# HG changeset patch
# User iuc
# Date 1522854224 14400
# Node ID 9cd9377881317310c1b68b3e7a28d56ae1990e64
# Parent 93f268840b0c067b2e8f3a5525ee410d4634d90b
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/mageck commit 49e456dda49db1f52fc876f406a10273a408b1a2
diff -r 93f268840b0c -r 9cd937788131 mageck_macros.xml
--- a/mageck_macros.xml Sat Feb 17 10:41:41 2018 -0500
+++ b/mageck_macros.xml Wed Apr 04 11:03:44 2018 -0400
@@ -1,27 +1,34 @@
+
0.5.7
+
mageck
-
+ numpy
r-gplots
r-xtable
+
- mageck -v
+ /dev/null | grep -v -i "WARNING: ")", xtable version" $(R --vanilla --slave -e "library(xtable); cat(sessionInfo()\$otherPkgs\$xtable\$Version)" 2> /dev/null | grep -v -i "WARNING: ")
+ ]]>
+
+
+
+
+
+
+
+
10.1186/s13059-014-0554-4
-
-
-
-
-
-
diff -r 93f268840b0c -r 9cd937788131 mageck_mle.xml
--- a/mageck_mle.xml Sat Feb 17 10:41:41 2018 -0500
+++ b/mageck_mle.xml Wed Apr 04 11:03:44 2018 -0400
@@ -30,10 +30,21 @@
--cnv-norm $adv.cnv_norm
#end if
---norm-method $adv.norm_method
---genes-varmodeling $adv.genes_var
---permutation-round $adv.permutation
---adjust-method $adv.adjust_method
+#if $adv.norm_method:
+ --norm-method $adv.norm_method
+#end if
+
+#if $adv.genes_var:
+ --genes-varmodeling $adv.genes_var
+#end if
+
+#if $adv.permutation:
+ --permutation-round $adv.permutation
+#end if
+
+#if $adv.adjust_method:
+ --adjust-method $adv.adjust_method
+#end if
#if $adv.sgrnaeff_file:
--sgrna-efficiency $adv.sgrnaeff_file
@@ -58,26 +69,32 @@
-
-
-
+
+ ^[\w,]+$
+
+
+ ^[\w]+$
+
+
+ ^[\w,]+$
+
-
+
+
-
-
-
+
+
-
-
+
+
@@ -168,9 +185,18 @@
**Outputs**
-If successful, MAGeCK mle will generate two files, the gene_summary file (including gene beta scores), and the sgrna_summary file (including sgRNA efficiency probability predictions).
+This tool outputs
+
+ * a ranked sgRNA Summary file
+ * a ranked Gene Summary file
-**Gene summary file (including beta scores)**
+Optionally, under **Output Options** you can choose to output
+
+ * a Log file of the analysis
+
+If successful, MAGeCK mle will generate two files, the Gene Summary file (including gene beta scores), and the sgRNA Summary file (including sgRNA efficiency probability predictions).
+
+**Gene Summary file (including beta scores)**
An example of the gene summary output file is below. This file includes the beta scores in two conditions specified in the design matrix (HL60|beta and KBM7|beta), and the associated statistics. For more information, check the output format specification of the **mageck test** *Gene Summary* file.
@@ -183,7 +209,7 @@
======== ========= ============= ========== ================ ============ ===================== ================= ============= =========== ================ ============ ===================== =================
-**sgRNA summary file (including sgRNA efficiency probability predictions)**
+**sgRNA Summary file (including sgRNA efficiency probability predictions)**
An example of the sgRNA ranking output is as follows:
diff -r 93f268840b0c -r 9cd937788131 test-data/in.test.sample.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/in.test.sample.txt Wed Apr 04 11:03:44 2018 -0400
@@ -0,0 +1,1000 @@
+sgRNA Gene HL60_initial KBM7_initial HL60_final KBM7_final
+A1CF_m52595977 A1CF 213 274 883 175
+A1CF_m52596017 A1CF 294 412 1554 1891
+A1CF_m52596056 A1CF 421 368 566 759
+A1CF_m52603842 A1CF 274 243 314 855
+A1CF_m52603847 A1CF 0 50 145 266
+A1CF_p52595870 A1CF 623 583 1503 1117
+A1CF_p52595881 A1CF 486 378 1775 1585
+A1CF_p52596023 A1CF 195 429 783 774
+A1CF_p52601638 A1CF 744 459 1233 2407
+A1CF_p52603829 A1CF 76 142 332 471
+AAAS_m53714382 AAAS 704 671 799 1426
+AAAS_m53715169 AAAS 651 627 797 1690
+AAAS_m53715176 AAAS 545 89 392 664
+AAAS_m53715212 AAAS 254 340 429 742
+AAAS_m53715238 AAAS 32 135 421 77
+AAAS_p53714367 AAAS 323 328 652 469
+AAAS_p53714374 AAAS 293 261 856 968
+AAAS_p53714391 AAAS 283 399 954 940
+AAAS_p53714405 AAAS 1119 856 2212 2715
+AAAS_p53714441 AAAS 273 327 1093 829
+AAK1_m69870049 AAK1 364 465 693 2006
+AAK1_m69870056 AAK1 635 707 2234 3515
+AAK1_m69870103 AAK1 485 452 914 629
+AAK1_m69870119 AAK1 405 275 806 837
+AAK1_m69870125 AAK1 274 350 1822 2101
+AAK1_m69870131 AAK1 754 763 1411 2637
+AAK1_m69870137 AAK1 905 294 512 798
+AAK1_p69870063 AAK1 330 167 364 1139
+AAK1_p69870070 AAK1 991 718 1790 1682
+AAK1_p69870105 AAK1 190 163 922 1118
+AATF_m35306444 AATF 449 456 1396 1402
+AATF_m35306475 AATF 493 612 1102 537
+AATF_m35306482 AATF 569 726 743 311
+AATF_m35306509 AATF 250 322 476 204
+AATF_m35307516 AATF 353 356 995 540
+AATF_m35307525 AATF 276 146 514 291
+AATF_p35306410 AATF 1426 1104 2494 1101
+AATF_p35306466 AATF 189 245 289 0
+AATF_p35307505 AATF 677 269 1154 481
+AATF_p35307527 AATF 1487 835 2761 3255
+AATK_m79102275 AATK 621 435 4568 1109
+AATK_m79102281 AATK 465 460 1736 2651
+AATK_m79102298 AATK 726 798 2538 2676
+AATK_m79102320 AATK 1003 655 1932 3223
+AATK_m79102325 AATK 633 722 1874 2030
+AATK_p79102286 AATK 1284 562 1844 1624
+AATK_p79102311 AATK 73 184 843 281
+AATK_p79104850 AATK 298 316 507 602
+AATK_p79104858 AATK 284 346 905 852
+AATK_p79104864 AATK 597 640 2244 2543
+ABCB8_m150725643 ABCB8 407 583 1738 2951
+ABCB8_m150725669 ABCB8 821 425 1510 1077
+ABCB8_m150730720 ABCB8 100 150 464 433
+ABCB8_p150725600 ABCB8 298 225 350 482
+ABCB8_p150725605 ABCB8 102 146 1396 428
+ABCB8_p150725612 ABCB8 251 107 1110 685
+ABCB8_p150725675 ABCB8 642 426 975 2565
+ABCB8_p150730680 ABCB8 526 481 1012 1108
+ABCB8_p150730705 ABCB8 743 522 1400 2105
+ABCB8_p150730712 ABCB8 170 215 999 1004
+ABCC1_m16043636 ABCC1 48 208 563 817
+ABCC1_m16043645 ABCC1 1095 551 1280 1793
+ABCC1_m16101705 ABCC1 873 593 1320 1374
+ABCC1_m16101777 ABCC1 476 410 1487 1117
+ABCC1_m16101788 ABCC1 453 296 754 857
+ABCC1_m16101799 ABCC1 497 511 779 1023
+ABCC1_p16043597 ABCC1 209 232 484 581
+ABCC1_p16101667 ABCC1 218 140 392 695
+ABCC1_p16101710 ABCC1 36 15 323 392
+ABCC1_p16101721 ABCC1 1007 684 1399 2741
+ABCF1_m30539291 ABCF1 147 163 305 871
+ABCF1_p30539251 ABCF1 767 675 589 647
+ABCF1_p30539272 ABCF1 756 585 1503 1612
+ABCF1_p30545181 ABCF1 792 678 2674 3651
+ABCF1_p30545587 ABCF1 33 140 1055 435
+ABCF1_p30545605 ABCF1 341 218 692 550
+ABCF1_p30545610 ABCF1 1344 1012 2581 2254
+ABCF1_p30545638 ABCF1 145 212 641 844
+ABCF1_p30545878 ABCF1 1369 1120 1687 755
+ABCF1_p30545888 ABCF1 180 199 701 335
+ABHD14B_m52004073 ABHD14B 322 191 616 546
+ABHD14B_m52004106 ABHD14B 304 222 823 595
+ABHD14B_m52004113 ABHD14B 394 367 1469 905
+ABHD14B_m52004122 ABHD14B 1220 1034 1559 2275
+ABHD14B_p52004005 ABHD14B 127 234 529 826
+ABHD14B_p52004011 ABHD14B 341 358 1060 1399
+ABHD14B_p52004019 ABHD14B 28 160 268 454
+ABHD14B_p52004061 ABHD14B 265 341 598 324
+ABHD14B_p52004076 ABHD14B 1415 1062 3286 2836
+ABHD14B_p52004124 ABHD14B 584 546 1254 1988
+ABI1_m27149710 ABI1 433 671 1145 574
+ABI1_m27149743 ABI1 961 396 1282 1685
+ABI1_m27149751 ABI1 839 489 1142 929
+ABI1_m27149764 ABI1 139 187 322 470
+ABI1_p27112164 ABI1 1163 932 1935 2368
+ABI1_p27112174 ABI1 1010 740 3367 2458
+ABI1_p27112180 ABI1 310 214 532 667
+ABI1_p27149695 ABI1 158 43 242 324
+ABI1_p27149701 ABI1 475 439 2839 1808
+ABI1_p27149733 ABI1 84 265 395 348
+ABL1_m133729449 ABL1 408 211 2194 1051
+ABL1_m133729456 ABL1 779 555 1893 837
+ABL1_m133729467 ABL1 670 449 2105 689
+ABL1_m133729488 ABL1 423 367 1091 62
+ABL1_m133729532 ABL1 953 825 3447 2456
+ABL1_m133729594 ABL1 531 283 1802 137
+ABL1_p133729441 ABL1 429 235 785 491
+ABL1_p133729469 ABL1 633 614 1603 2103
+ABL1_p133729492 ABL1 752 660 1616 701
+ABL1_p133729502 ABL1 527 298 1071 400
+ABL2_m179100447 ABL2 970 578 2465 2558
+ABL2_m179100544 ABL2 442 151 868 527
+ABL2_m179100554 ABL2 718 407 1451 1761
+ABL2_m179100597 ABL2 423 431 1458 1285
+ABL2_p179095768 ABL2 364 325 1280 822
+ABL2_p179100489 ABL2 1567 840 2727 3472
+ABL2_p179100503 ABL2 647 560 1579 881
+ABL2_p179100524 ABL2 471 266 1198 1935
+ABL2_p179100556 ABL2 412 283 1336 813
+ABL2_p179100578 ABL2 424 321 871 886
+ABLIM2_m8108265 ABLIM2 1080 672 1816 2314
+ABLIM2_m8108274 ABLIM2 372 784 2237 2717
+ABLIM2_m8108279 ABLIM2 458 338 755 1004
+ABLIM2_m8108294 ABLIM2 709 1285 2947 3905
+ABLIM2_m8108316 ABLIM2 198 173 245 304
+ABLIM2_m8160405 ABLIM2 909 1005 2217 2001
+ABLIM2_p8108286 ABLIM2 637 561 1768 2749
+ABLIM2_p8108299 ABLIM2 639 836 2576 3115
+ABLIM2_p8108320 ABLIM2 102 38 155 410
+ABLIM2_p8108331 ABLIM2 885 652 2079 1885
+ABT1_m26597238 ABT1 332 207 495 771
+ABT1_m26597359 ABT1 244 222 940 469
+ABT1_m26597388 ABT1 1186 1115 1327 492
+ABT1_p26597221 ABT1 1087 825 1689 1735
+ABT1_p26597240 ABT1 81 213 294 225
+ABT1_p26597266 ABT1 671 420 520 528
+ABT1_p26597293 ABT1 356 391 534 1045
+ABT1_p26597300 ABT1 1063 430 669 385
+ABT1_p26597313 ABT1 21 101 378 323
+ABT1_p26597361 ABT1 231 252 492 360
+ABTB1_m127395233 ABTB1 407 308 765 550
+ABTB1_m127395403 ABTB1 576 877 765 2182
+ABTB1_m127395808 ABTB1 806 366 1408 1592
+ABTB1_m127395813 ABTB1 335 199 1368 1279
+ABTB1_m127395855 ABTB1 381 500 1765 1327
+ABTB1_m127395860 ABTB1 643 621 1404 2053
+ABTB1_p127395220 ABTB1 444 627 1291 518
+ABTB1_p127395242 ABTB1 573 802 1353 1655
+ABTB1_p127395252 ABTB1 358 225 652 1348
+ABTB1_p127395834 ABTB1 342 485 656 1442
+ACAD11_m132378487 ACAD11 372 404 1310 1207
+ACAD11_m132378519 ACAD11 273 248 719 639
+ACAD11_m132378564 ACAD11 673 870 1657 2599
+ACAD11_m132378578 ACAD11 358 334 789 810
+ACAD11_p132378460 ACAD11 1103 627 1294 1663
+ACAD11_p132378489 ACAD11 510 745 1345 1522
+ACAD11_p132378501 ACAD11 725 418 1432 1513
+ACAD11_p132378525 ACAD11 557 648 1139 2025
+ACAD11_p132378547 ACAD11 35 262 398 250
+ACAD11_p132378566 ACAD11 462 438 713 1096
+ACAD9_m128598565 ACAD9 503 521 4007 3584
+ACAD9_m128598607 ACAD9 91 121 326 476
+ACAD9_m128598614 ACAD9 460 544 2733 923
+ACAD9_m128598631 ACAD9 272 343 446 699
+ACAD9_m128598636 ACAD9 388 297 489 253
+ACAD9_p128598519 ACAD9 433 425 921 393
+ACAD9_p128598525 ACAD9 391 299 430 1624
+ACAD9_p128598545 ACAD9 564 619 1072 706
+ACAD9_p128598551 ACAD9 789 752 1776 2200
+ACAD9_p128598592 ACAD9 627 436 791 821
+ACAT2_m160183168 ACAT2 448 147 568 619
+ACAT2_m160183956 ACAT2 542 577 2289 1422
+ACAT2_m160183968 ACAT2 1236 1603 2875 3082
+ACAT2_p160183107 ACAT2 1384 1266 1743 3058
+ACAT2_p160183121 ACAT2 1135 1085 3564 2633
+ACAT2_p160183133 ACAT2 354 378 1046 1292
+ACAT2_p160183141 ACAT2 846 475 973 2007
+ACAT2_p160183152 ACAT2 1487 1057 3365 4954
+ACAT2_p160183940 ACAT2 15 0 41 39
+ACAT2_p160183972 ACAT2 94 156 700 1177
+ACBD6_m180471277 ACBD6 800 292 1321 827
+ACBD6_m180471338 ACBD6 764 459 692 1002
+ACBD6_m180471378 ACBD6 403 325 1241 864
+ACBD6_p180471251 ACBD6 332 115 896 609
+ACBD6_p180471256 ACBD6 73 161 877 1202
+ACBD6_p180471263 ACBD6 242 161 441 371
+ACBD6_p180471279 ACBD6 539 700 1081 808
+ACBD6_p180471286 ACBD6 492 567 1482 749
+ACBD6_p180471344 ACBD6 708 728 2207 2977
+ACBD6_p180471350 ACBD6 413 303 1196 1451
+ACD_m67694254 ACD 799 526 2606 3199
+ACD_m67694260 ACD 809 931 2093 1708
+ACD_m67694316 ACD 190 254 648 674
+ACD_m67694376 ACD 1262 800 1718 2069
+ACD_p67694194 ACD 979 589 1841 2020
+ACD_p67694285 ACD 414 279 874 1102
+ACD_p67694333 ACD 209 137 249 449
+ACD_p67694350 ACD 370 138 469 679
+ACD_p67694355 ACD 512 448 1735 1603
+ACD_p67694362 ACD 1082 618 2113 2505
+ACHE_m100491721 ACHE 732 492 1307 991
+ACHE_m100491729 ACHE 331 468 1364 1276
+ACHE_m100491735 ACHE 1034 902 2107 2308
+ACHE_m100491767 ACHE 1059 990 1539 1648
+ACHE_m100491773 ACHE 384 219 257 395
+ACHE_m100491779 ACHE 191 296 473 883
+ACHE_m100491816 ACHE 201 237 603 592
+ACHE_p100491631 ACHE 368 331 1066 1230
+ACHE_p100491656 ACHE 1787 961 2773 4492
+ACHE_p100491821 ACHE 588 627 606 579
+ACIN1_m23535193 ACIN1 382 464 679 1012
+ACIN1_m23538698 ACIN1 2330 2150 3158 1206
+ACIN1_m23538715 ACIN1 576 555 531 727
+ACIN1_m23538803 ACIN1 1655 1195 1692 272
+ACIN1_m23538815 ACIN1 890 1231 2350 1743
+ACIN1_p23538701 ACIN1 276 151 270 192
+ACIN1_p23538719 ACIN1 436 315 1128 1105
+ACIN1_p23538730 ACIN1 644 265 1051 800
+ACIN1_p23538735 ACIN1 168 100 45 0
+ACIN1_p23538745 ACIN1 387 345 894 473
+ACLY_m40069993 ACLY 863 795 1801 1055
+ACLY_m40070008 ACLY 223 256 82 42
+ACLY_m40070029 ACLY 90 136 195 115
+ACLY_m40070097 ACLY 337 330 443 426
+ACLY_m40070116 ACLY 687 621 1961 1756
+ACLY_p40069998 ACLY 597 403 853 1039
+ACLY_p40070033 ACLY 1085 624 960 223
+ACLY_p40070039 ACLY 214 142 141 629
+ACLY_p40070062 ACLY 349 152 326 221
+ACLY_p40070105 ACLY 518 268 887 1043
+ACO2_m41865159 ACO2 811 495 1351 659
+ACO2_m41895784 ACO2 561 488 1799 2344
+ACO2_m41895810 ACO2 1517 1009 2303 2170
+ACO2_m41895824 ACO2 402 188 463 1188
+ACO2_m41903807 ACO2 323 634 1371 1351
+ACO2_p41865164 ACO2 440 175 1056 852
+ACO2_p41895716 ACO2 206 196 641 842
+ACO2_p41895844 ACO2 180 296 596 1008
+ACO2_p41903797 ACO2 386 375 598 175
+ACO2_p41903813 ACO2 711 275 1887 1213
+ACP1_m264983 ACP1 1432 979 2488 3262
+ACP1_m264989 ACP1 991 751 2780 2161
+ACP1_m272095 ACP1 348 377 785 1370
+ACP1_m272137 ACP1 1177 407 1252 1058
+ACP1_p264954 ACP1 862 787 1473 2180
+ACP1_p272032 ACP1 1100 804 2170 2224
+ACP1_p272042 ACP1 587 667 1412 1531
+ACP1_p272054 ACP1 439 242 245 784
+ACP1_p272099 ACP1 240 183 548 776
+ACP1_p272185 ACP1 1106 449 1508 2250
+ACRC_m70811980 ACRC 314 283 706 1554
+ACRC_m70814198 ACRC 52 51 709 624
+ACRC_p70800656 ACRC 176 386 846 980
+ACRC_p70800697 ACRC 158 384 437 817
+ACRC_p70800703 ACRC 948 829 1648 931
+ACRC_p70800708 ACRC 1630 1375 3904 4302
+ACRC_p70811990 ACRC 337 341 1838 2827
+ACRC_p70814182 ACRC 464 463 2492 2331
+ACRC_p70814187 ACRC 654 618 1521 1582
+ACRC_p70814200 ACRC 1320 726 1494 1929
+ACSL6_m131326625 ACSL6 436 107 1422 1026
+ACSL6_m131326630 ACSL6 702 341 1272 2201
+ACSL6_m131326651 ACSL6 429 390 1691 2488
+ACSL6_m131329874 ACSL6 541 602 2163 1428
+ACSL6_m131329908 ACSL6 688 488 884 734
+ACSL6_p131329816 ACSL6 1223 605 1955 1719
+ACSL6_p131329824 ACSL6 699 551 2121 725
+ACSL6_p131329830 ACSL6 524 414 824 706
+ACSL6_p131329859 ACSL6 165 127 515 533
+ACSL6_p131329878 ACSL6 618 808 1583 2013
+ACSS2_m33470722 ACSS2 500 202 859 662
+ACSS2_m33500924 ACSS2 405 333 1683 1551
+ACSS2_m33500940 ACSS2 1126 531 1695 3562
+ACSS2_m33500955 ACSS2 426 498 820 1500
+ACSS2_m33501214 ACSS2 463 421 845 1776
+ACSS2_m33501222 ACSS2 451 438 1371 1376
+ACSS2_p33470688 ACSS2 599 350 1065 1819
+ACSS2_p33500893 ACSS2 64 252 1128 1621
+ACSS2_p33500928 ACSS2 272 454 1819 1851
+ACSS2_p33501184 ACSS2 475 299 799 608
+ACTL6A_m179287950 ACTL6A 259 218 304 159
+ACTL6A_m179287986 ACTL6A 450 202 470 590
+ACTL6A_p179287878 ACTL6A 353 283 157 417
+ACTL6A_p179287892 ACTL6A 283 377 1190 1878
+ACTL6A_p179287902 ACTL6A 513 498 988 1159
+ACTL6A_p179287911 ACTL6A 872 670 1947 1268
+ACTL6A_p179287920 ACTL6A 818 657 1910 1654
+ACTL6A_p179287966 ACTL6A 1006 410 869 304
+ACTL6A_p179287976 ACTL6A 216 555 1954 1047
+ACTL6A_p179291144 ACTL6A 126 253 232 721
+ACTL6B_m100253076 ACTL6B 629 628 2063 1552
+ACTL6B_m100253081 ACTL6B 396 389 750 916
+ACTL6B_m100253086 ACTL6B 434 521 1882 2074
+ACTL6B_m100253168 ACTL6B 511 529 748 2164
+ACTL6B_m100253443 ACTL6B 758 723 2678 2516
+ACTL6B_m100253971 ACTL6B 329 258 361 1120
+ACTL6B_p100253037 ACTL6B 949 460 1018 2309
+ACTL6B_p100253066 ACTL6B 669 576 889 767
+ACTL6B_p100253094 ACTL6B 643 793 2197 1129
+ACTL6B_p100253446 ACTL6B 823 466 1720 826
+ACTL7A_m111624641 ACTL7A 1314 876 2510 3213
+ACTL7A_m111624669 ACTL7A 377 215 956 842
+ACTL7A_m111624684 ACTL7A 363 196 962 1151
+ACTL7A_m111624726 ACTL7A 276 171 661 450
+ACTL7A_m111624736 ACTL7A 594 467 578 763
+ACTL7A_p111624607 ACTL7A 236 403 885 1854
+ACTL7A_p111624631 ACTL7A 449 404 599 568
+ACTL7A_p111624686 ACTL7A 232 67 168 519
+ACTL7A_p111624691 ACTL7A 228 280 953 1363
+ACTL7A_p111624699 ACTL7A 826 437 1417 950
+ACTN1_m69392359 ACTN1 371 199 1423 1037
+ACTN1_m69392382 ACTN1 466 515 1342 2479
+ACTN1_m69445694 ACTN1 212 355 816 193
+ACTN1_m69445700 ACTN1 476 322 1643 1666
+ACTN1_m69445718 ACTN1 739 356 1746 1278
+ACTN1_m69445724 ACTN1 1001 742 2437 2097
+ACTN1_p69392370 ACTN1 1446 919 3111 3490
+ACTN1_p69445679 ACTN1 175 74 381 334
+ACTN1_p69445708 ACTN1 122 142 395 420
+ACTN1_p69445745 ACTN1 591 419 1213 1105
+ACTN4_m39138399 ACTN4 540 400 1210 1730
+ACTN4_m39138430 ACTN4 111 149 596 620
+ACTN4_m39138527 ACTN4 146 90 398 67
+ACTN4_p39138381 ACTN4 447 358 1075 1450
+ACTN4_p39138403 ACTN4 570 837 1744 2822
+ACTN4_p39138433 ACTN4 590 473 1627 1689
+ACTN4_p39138459 ACTN4 1072 1136 1897 2800
+ACTN4_p39138465 ACTN4 1160 610 1726 2233
+ACTN4_p39138476 ACTN4 306 268 1675 1709
+ACTN4_p39138482 ACTN4 927 566 2530 2890
+ACTR1A_m104248862 ACTR1A 719 1214 2213 2147
+ACTR1A_m104250350 ACTR1A 284 126 189 193
+ACTR1A_m104250365 ACTR1A 274 91 1128 1252
+ACTR1A_p104248833 ACTR1A 547 420 1032 1967
+ACTR1A_p104248866 ACTR1A 664 375 741 301
+ACTR1A_p104250290 ACTR1A 412 416 3242 1959
+ACTR1A_p104250304 ACTR1A 445 586 1731 2020
+ACTR1A_p104262351 ACTR1A 662 619 1218 4097
+ACTR1A_p104262374 ACTR1A 910 407 1189 1732
+ACTR1A_p104262383 ACTR1A 844 471 342 627
+ACTR3_m114684932 ACTR3 697 767 1401 693
+ACTR3_m114688941 ACTR3 781 589 1286 326
+ACTR3_p114674498 ACTR3 896 664 2125 1851
+ACTR3_p114684915 ACTR3 609 464 1110 998
+ACTR3_p114684941 ACTR3 648 616 1964 2548
+ACTR3_p114684946 ACTR3 524 309 1193 643
+ACTR3_p114684953 ACTR3 58 358 287 1091
+ACTR3_p114688931 ACTR3 491 433 927 1553
+ACTR3_p114691883 ACTR3 369 437 663 816
+ACTR3_p114691894 ACTR3 1477 1267 2229 2034
+ACTR5_m37377141 ACTR5 589 527 2529 2963
+ACTR5_m37377155 ACTR5 65 208 659 363
+ACTR5_m37377161 ACTR5 233 309 842 355
+ACTR5_m37377171 ACTR5 298 250 764 685
+ACTR5_m37377189 ACTR5 462 436 2502 1189
+ACTR5_p37377163 ACTR5 362 463 1571 789
+ACTR5_p37377178 ACTR5 258 374 1370 888
+ACTR5_p37377198 ACTR5 254 270 673 1140
+ACTR5_p37377204 ACTR5 198 172 570 543
+ACTR5_p37377211 ACTR5 695 416 755 492
+ACTR8_m53916047 ACTR8 1690 1323 3444 1592
+ACTR8_m53916057 ACTR8 675 566 1179 350
+ACTR8_m53916067 ACTR8 862 651 398 74
+ACTR8_m53916073 ACTR8 1021 741 1269 2580
+ACTR8_m53916081 ACTR8 1310 1157 309 411
+ACTR8_m53916091 ACTR8 239 440 361 1091
+ACTR8_m53916096 ACTR8 1170 567 565 388
+ACTR8_m53916103 ACTR8 615 814 2350 1844
+ACTR8_m53916111 ACTR8 443 609 913 1874
+ACTR8_m53916121 ACTR8 194 230 157 78
+ACTRT3_m169487192 ACTRT3 347 97 346 310
+ACTRT3_m169487204 ACTRT3 257 156 950 1253
+ACTRT3_m169487242 ACTRT3 1477 907 1672 2552
+ACTRT3_m169487247 ACTRT3 294 470 457 812
+ACTRT3_m169487252 ACTRT3 193 481 553 1045
+ACTRT3_m169487267 ACTRT3 432 381 1343 1621
+ACTRT3_m169487273 ACTRT3 549 406 282 1198
+ACTRT3_m169487289 ACTRT3 760 300 752 681
+ACTRT3_p169487206 ACTRT3 24 229 715 1043
+ACTRT3_p169487280 ACTRT3 1000 564 2005 1704
+ACVR1B_m52369170 ACVR1B 280 468 1538 2861
+ACVR1B_m52369187 ACVR1B 707 652 1605 1647
+ACVR1B_m52369192 ACVR1B 430 268 2364 748
+ACVR1B_m52369211 ACVR1B 1029 754 1684 2786
+ACVR1B_m52369226 ACVR1B 35 205 515 205
+ACVR1B_m52369237 ACVR1B 1002 865 1931 1920
+ACVR1B_p52369196 ACVR1B 276 160 275 415
+ACVR1B_p52369243 ACVR1B 471 422 963 783
+ACVR1B_p52369255 ACVR1B 114 94 70 263
+ACVR1B_p52369266 ACVR1B 796 679 2414 2199
+ACVR1C_m158401016 ACVR1C 305 258 723 1114
+ACVR1C_m158401030 ACVR1C 748 808 2126 3206
+ACVR1C_m158401075 ACVR1C 193 176 471 1063
+ACVR1C_m158401097 ACVR1C 654 444 1557 1665
+ACVR1C_m158401113 ACVR1C 224 185 486 717
+ACVR1C_m158443700 ACVR1C 675 359 1390 2446
+ACVR1C_m158443841 ACVR1C 323 290 1419 1520
+ACVR1C_p158443781 ACVR1C 335 259 1156 1715
+ACVR1C_p158443786 ACVR1C 959 517 2009 2015
+ACVR1C_p158443795 ACVR1C 1008 588 2106 2524
+ACVR1_m158637033 ACVR1 652 426 2567 2204
+ACVR1_m158637046 ACVR1 485 382 2055 1724
+ACVR1_m158637054 ACVR1 198 488 904 680
+ACVR1_m158637066 ACVR1 483 371 1070 1150
+ACVR1_m158655997 ACVR1 918 1304 2692 3010
+ACVR1_p158637019 ACVR1 455 605 1145 1331
+ACVR1_p158637035 ACVR1 1370 776 2676 3298
+ACVR1_p158637068 ACVR1 469 810 2288 2807
+ACVR1_p158655928 ACVR1 196 173 851 587
+ACVR1_p158655958 ACVR1 279 203 1070 569
+ACVR2A_m148602752 ACVR2A 955 561 1182 1126
+ACVR2A_m148602767 ACVR2A 1084 799 1782 3155
+ACVR2A_m148653941 ACVR2A 396 368 746 2145
+ACVR2A_m148653961 ACVR2A 587 243 1032 954
+ACVR2A_p148602720 ACVR2A 961 403 2354 3163
+ACVR2A_p148602754 ACVR2A 350 142 731 943
+ACVR2A_p148653859 ACVR2A 169 350 959 1370
+ACVR2A_p148653946 ACVR2A 648 263 1457 2080
+ACVR2A_p148653965 ACVR2A 390 95 190 583
+ACVR2A_p148653997 ACVR2A 1091 1020 2469 2845
+ACVR2B_m38495825 ACVR2B 1404 1332 3150 2677
+ACVR2B_m38518828 ACVR2B 275 617 2219 2134
+ACVR2B_m38518849 ACVR2B 440 415 1134 662
+ACVR2B_p38495805 ACVR2B 547 437 872 1040
+ACVR2B_p38495827 ACVR2B 789 618 1598 2756
+ACVR2B_p38518810 ACVR2B 780 728 2390 2354
+ACVR2B_p38518817 ACVR2B 861 991 2617 3970
+ACVR2B_p38518836 ACVR2B 997 438 1180 1663
+ACVR2B_p38518841 ACVR2B 400 279 1162 1254
+ACVR2B_p38518854 ACVR2B 1460 918 2715 3235
+ACVRL1_m52306276 ACVRL1 627 496 2249 2456
+ACVRL1_m52306307 ACVRL1 557 550 1651 1462
+ACVRL1_m52306881 ACVRL1 1133 621 2525 2059
+ACVRL1_m52306910 ACVRL1 868 640 2322 2264
+ACVRL1_m52306921 ACVRL1 504 296 2326 958
+ACVRL1_p52306245 ACVRL1 569 548 1736 2092
+ACVRL1_p52306281 ACVRL1 813 505 2675 2225
+ACVRL1_p52306287 ACVRL1 1148 859 2205 3686
+ACVRL1_p52306296 ACVRL1 906 633 1150 1272
+ACVRL1_p52306883 ACVRL1 1056 636 1842 2022
+ADAD1_m123301295 ADAD1 405 500 1518 1011
+ADAD1_m123301308 ADAD1 531 425 878 2224
+ADAD1_m123301332 ADAD1 711 630 1699 1668
+ADAD1_m123301345 ADAD1 350 264 1162 654
+ADAD1_m123301366 ADAD1 358 314 1423 1337
+ADAD1_p123301314 ADAD1 991 793 2078 2170
+ADAD1_p123301335 ADAD1 538 230 595 508
+ADAD1_p123301349 ADAD1 651 161 802 1162
+ADAD1_p123301358 ADAD1 1190 1074 3236 4172
+ADAD1_p123301373 ADAD1 628 471 1456 1346
+ADAM10_m58974490 ADAM10 417 394 676 702
+ADAM10_m59009777 ADAM10 367 575 1729 1785
+ADAM10_m59009866 ADAM10 415 353 538 1216
+ADAM10_m59009883 ADAM10 815 1060 2685 3758
+ADAM10_m59041689 ADAM10 61 56 79 309
+ADAM10_m59041696 ADAM10 340 258 649 592
+ADAM10_p58974401 ADAM10 659 487 936 448
+ADAM10_p58974481 ADAM10 911 649 2327 2141
+ADAM10_p59009761 ADAM10 246 134 293 508
+ADAM10_p59009767 ADAM10 603 423 1536 912
+ADAM12_m128018982 ADAM12 438 199 661 612
+ADAM12_m128019019 ADAM12 753 735 1714 1670
+ADAM12_m128019025 ADAM12 381 485 1516 1073
+ADAM12_m128076635 ADAM12 242 399 825 1111
+ADAM12_m128076658 ADAM12 523 432 2270 2731
+ADAM12_p128018991 ADAM12 35 39 132 389
+ADAM12_p128019039 ADAM12 1241 459 1049 1058
+ADAM12_p128076618 ADAM12 82 131 305 410
+ADAM12_p128076641 ADAM12 768 751 2339 3211
+ADAM12_p128076650 ADAM12 530 365 673 1328
+ADAMTS5_m28338537 ADAMTS5 668 722 1079 2252
+ADAMTS5_m28338697 ADAMTS5 727 422 859 1530
+ADAMTS5_m28338702 ADAMTS5 410 280 994 1053
+ADAMTS5_p28338524 ADAMTS5 614 586 1600 1039
+ADAMTS5_p28338585 ADAMTS5 662 529 853 1072
+ADAMTS5_p28338596 ADAMTS5 572 322 592 1002
+ADAMTS5_p28338607 ADAMTS5 758 530 2009 1206
+ADAMTS5_p28338612 ADAMTS5 78 166 278 479
+ADAMTS5_p28338620 ADAMTS5 272 118 566 822
+ADAMTS5_p28338667 ADAMTS5 759 520 1914 3378
+ADAP1_m975089 ADAP1 321 356 830 1158
+ADAP1_m975116 ADAP1 399 189 602 758
+ADAP1_m975132 ADAP1 651 530 1919 1445
+ADAP1_m994042 ADAP1 199 208 720 1240
+ADAP1_m994066 ADAP1 114 38 324 622
+ADAP1_m994071 ADAP1 781 405 416 603
+ADAP1_m994091 ADAP1 598 686 569 1671
+ADAP1_m994101 ADAP1 781 449 1441 1951
+ADAP1_m994106 ADAP1 300 372 1070 872
+ADAP1_p975103 ADAP1 619 400 837 2124
+ADARB1_m46591572 ADARB1 140 105 358 629
+ADARB1_m46595675 ADARB1 387 265 1117 697
+ADARB1_m46595697 ADARB1 485 319 952 1089
+ADARB1_m46595715 ADARB1 510 213 749 1177
+ADARB1_m46595721 ADARB1 156 414 1880 1598
+ADARB1_m46595779 ADARB1 453 98 304 253
+ADARB1_p46595645 ADARB1 738 566 2401 2617
+ADARB1_p46595700 ADARB1 503 515 1573 1321
+ADARB1_p46595705 ADARB1 1352 1069 2843 4330
+ADARB1_p46595724 ADARB1 234 73 485 397
+ADARB2_m1779246 ADARB2 1268 893 2792 2559
+ADARB2_m1779251 ADARB2 505 337 1496 1434
+ADARB2_m1779266 ADARB2 1067 1173 2870 3299
+ADARB2_m1779272 ADARB2 693 289 1077 1441
+ADARB2_m1779308 ADARB2 776 671 1395 1709
+ADARB2_m1779330 ADARB2 92 67 557 699
+ADARB2_m1779337 ADARB2 453 395 1564 1305
+ADARB2_p1421307 ADARB2 285 169 597 1128
+ADARB2_p1421336 ADARB2 382 306 1398 1015
+ADARB2_p1779233 ADARB2 301 129 627 1138
+ADAR_m154574098 ADAR 1070 579 1931 1523
+ADAR_m154574103 ADAR 90 75 441 1151
+ADAR_m154574108 ADAR 1085 615 2361 1748
+ADAR_m154574165 ADAR 458 292 865 1012
+ADAR_m154574219 ADAR 432 715 2566 1758
+ADAR_p154574043 ADAR 521 589 1702 1435
+ADAR_p154574114 ADAR 68 110 61 35
+ADAR_p154574121 ADAR 0 5 0 0
+ADAR_p154574126 ADAR 233 227 372 594
+ADAR_p154574157 ADAR 701 294 1072 1160
+ADCK1_m78285328 ADCK1 451 568 1746 2962
+ADCK1_m78285358 ADCK1 1053 1107 2964 4114
+ADCK1_m78285376 ADCK1 993 664 2055 2136
+ADCK1_m78285413 ADCK1 812 763 2571 3331
+ADCK1_p78285311 ADCK1 591 395 1142 1055
+ADCK1_p78285331 ADCK1 543 433 2344 3069
+ADCK1_p78285341 ADCK1 795 511 1394 1709
+ADCK1_p78285386 ADCK1 551 387 1076 1513
+ADCK1_p78285402 ADCK1 848 424 2063 2210
+ADCK1_p78285416 ADCK1 562 449 1550 3612
+ADCK2_m140373155 ADCK2 53 55 158 371
+ADCK2_m140373168 ADCK2 469 309 710 1295
+ADCK2_m140373177 ADCK2 396 453 1181 747
+ADCK2_m140373210 ADCK2 587 354 2377 1644
+ADCK2_m140373220 ADCK2 235 328 1346 846
+ADCK2_m140373231 ADCK2 894 647 1868 2104
+ADCK2_p140373122 ADCK2 394 525 1206 1142
+ADCK2_p140373137 ADCK2 132 30 193 44
+ADCK2_p140373158 ADCK2 570 537 1365 1700
+ADCK2_p140373194 ADCK2 854 572 2422 1834
+ADCK3_m227149096 ADCK3 184 234 688 919
+ADCK3_m227149144 ADCK3 179 95 300 405
+ADCK3_m227149153 ADCK3 844 1373 2964 3638
+ADCK3_m227149163 ADCK3 759 599 2130 3197
+ADCK3_p227149079 ADCK3 1573 613 2063 2888
+ADCK3_p227149104 ADCK3 1108 940 3375 3744
+ADCK3_p227149124 ADCK3 822 569 1637 1858
+ADCK3_p227149133 ADCK3 493 365 1114 1747
+ADCK3_p227149155 ADCK3 1548 1255 4648 5233
+ADCK3_p227149165 ADCK3 380 472 1686 2046
+ADCK4_m41220243 ADCK4 565 487 2139 1295
+ADCK4_m41220249 ADCK4 1008 1123 3240 3165
+ADCK4_m41220284 ADCK4 840 732 2152 3902
+ADCK4_m41220291 ADCK4 153 106 1110 142
+ADCK4_m41220465 ADCK4 553 476 1500 1747
+ADCK4_m41220474 ADCK4 1346 986 4215 4983
+ADCK4_m41220523 ADCK4 385 437 1392 779
+ADCK4_p41220276 ADCK4 463 301 873 1793
+ADCK4_p41220422 ADCK4 110 188 436 813
+ADCK4_p41220480 ADCK4 1717 1377 3413 2651
+ADCK5_m145603095 ADCK5 617 573 1345 2054
+ADCK5_m145603137 ADCK5 813 610 1046 1919
+ADCK5_m145603170 ADCK5 584 452 1694 958
+ADCK5_m145608301 ADCK5 715 396 2393 2309
+ADCK5_m145608343 ADCK5 637 445 2314 2374
+ADCK5_p145597774 ADCK5 392 305 1063 531
+ADCK5_p145603106 ADCK5 1009 755 3670 2825
+ADCK5_p145603142 ADCK5 871 833 2002 2685
+ADCK5_p145608305 ADCK5 256 349 597 165
+ADCK5_p145608311 ADCK5 409 418 1942 1575
+ADCY1_m45614206 ADCY1 122 176 649 351
+ADCY1_m45614243 ADCY1 688 682 769 1474
+ADCY1_m45614270 ADCY1 454 346 861 1526
+ADCY1_m45614323 ADCY1 483 514 1591 2080
+ADCY1_p45614127 ADCY1 1174 1279 2832 2521
+ADCY1_p45614255 ADCY1 307 465 1300 901
+ADCY1_p45614284 ADCY1 296 284 589 810
+ADCY1_p45614294 ADCY1 102 176 456 419
+ADCY1_p45614309 ADCY1 265 110 279 66
+ADCY1_p45614315 ADCY1 2 41 334 327
+ADD1_m2877698 ADD1 325 227 747 430
+ADD1_m2877722 ADD1 326 204 806 817
+ADD1_m2877771 ADD1 361 456 1293 1306
+ADD1_m2877776 ADD1 385 247 855 962
+ADD1_p2877627 ADD1 161 175 797 1406
+ADD1_p2877644 ADD1 558 574 1946 1334
+ADD1_p2877730 ADD1 132 14 378 366
+ADD1_p2877736 ADD1 751 456 1220 969
+ADD1_p2877743 ADD1 390 787 1155 1591
+ADD1_p2877761 ADD1 960 365 1696 1882
+ADD3_m111860427 ADD3 193 292 1082 1216
+ADD3_m111860445 ADD3 862 391 1646 934
+ADD3_m111860450 ADD3 1087 846 2617 3137
+ADD3_m111860456 ADD3 1010 495 2002 1201
+ADD3_m111860540 ADD3 794 741 2167 1575
+ADD3_p111860411 ADD3 404 470 829 1630
+ADD3_p111860500 ADD3 351 591 1798 1978
+ADD3_p111860505 ADD3 665 476 984 1023
+ADD3_p111860545 ADD3 940 681 1977 2029
+ADD3_p111860553 ADD3 1280 776 2512 1755
+ADH5_m100003154 ADH5 381 424 416 798
+ADH5_m100003254 ADH5 802 700 1376 1879
+ADH5_m100006267 ADH5 911 907 3313 3502
+ADH5_m100006354 ADH5 971 652 2604 2435
+ADH5_m100009841 ADH5 1322 1273 3324 3483
+ADH5_p100002504 ADH5 455 404 1225 1641
+ADH5_p100002510 ADH5 302 136 716 1270
+ADH5_p100002584 ADH5 1479 666 2178 2515
+ADH5_p100003219 ADH5 215 330 71 223
+ADH5_p100003224 ADH5 378 204 542 1124
+ADH7_m100349694 ADH7 552 581 1627 1566
+ADH7_m100350690 ADH7 116 403 581 668
+ADH7_m100350735 ADH7 553 374 1228 793
+ADH7_m100350762 ADH7 1263 889 2255 2111
+ADH7_p100349698 ADH7 740 477 1576 2712
+ADH7_p100349706 ADH7 316 222 272 956
+ADH7_p100349757 ADH7 412 324 814 1257
+ADH7_p100350692 ADH7 398 255 649 1596
+ADH7_p100350718 ADH7 117 181 363 114
+ADH7_p100350724 ADH7 233 217 712 560
+ADI1_m3517677 ADI1 282 275 359 706
+ADI1_m3523156 ADI1 523 407 1020 1658
+ADI1_m3523162 ADI1 403 400 575 1011
+ADI1_m3523239 ADI1 394 178 644 1113
+ADI1_m3523246 ADI1 545 375 1984 1698
+ADI1_m3523251 ADI1 1062 1025 3383 3536
+ADI1_p3517642 ADI1 178 225 644 1989
+ADI1_p3517660 ADI1 667 470 1496 1344
+ADI1_p3523164 ADI1 762 685 1012 1748
+ADI1_p3523171 ADI1 433 88 894 437
+ADIRF_m88728302 ADIRF 335 125 491 180
+ADIRF_m88728350 ADIRF 166 135 207 305
+ADIRF_m88729968 ADIRF 500 379 984 823
+ADIRF_p88728292 ADIRF 731 535 1745 1300
+ADIRF_p88728315 ADIRF 478 569 2047 1778
+ADIRF_p88728321 ADIRF 1121 428 1087 1063
+ADIRF_p88729942 ADIRF 647 487 962 1344
+ADIRF_p88729951 ADIRF 296 245 437 594
+ADIRF_p88729975 ADIRF 61 118 331 532
+ADIRF_p88729984 ADIRF 904 885 1780 2371
+ADK_m75960552 ADK 1002 1030 2002 2299
+ADK_m75960590 ADK 142 37 463 612
+ADK_m76153995 ADK 688 657 1035 1504
+ADK_m76154033 ADK 379 386 1387 1782
+ADK_p75960554 ADK 247 465 1168 611
+ADK_p76074446 ADK 1024 254 1036 1732
+ADK_p76074475 ADK 135 16 396 200
+ADK_p76074481 ADK 298 42 404 404
+ADK_p76153940 ADK 547 266 2118 2103
+ADK_p76154015 ADK 309 276 1421 1198
+ADNP2_m77891006 ADNP2 0 0 25 295
+ADNP2_p77875445 ADNP2 446 349 891 1167
+ADNP2_p77875475 ADNP2 169 60 454 806
+ADNP2_p77875482 ADNP2 382 220 761 1355
+ADNP2_p77875499 ADNP2 507 346 719 1609
+ADNP2_p77875511 ADNP2 880 734 1596 2475
+ADNP2_p77890985 ADNP2 528 721 1784 2201
+ADNP2_p77891013 ADNP2 505 342 833 1052
+ADNP2_p77891042 ADNP2 162 131 662 956
+ADNP2_p77891053 ADNP2 241 181 536 504
+ADNP_m49511043 ADNP 278 295 767 1226
+ADNP_m49518579 ADNP 1228 808 2714 3762
+ADNP_m49518587 ADNP 2053 1488 2908 6245
+ADNP_m49520451 ADNP 1122 441 1226 2328
+ADNP_m49520507 ADNP 653 787 2266 4913
+ADNP_p49510837 ADNP 337 170 534 970
+ADNP_p49510899 ADNP 1015 750 3309 3466
+ADNP_p49510949 ADNP 292 501 900 1980
+ADNP_p49511011 ADNP 291 323 1039 1572
+ADNP_p49520498 ADNP 470 432 1649 1736
+ADPRHL2_m36554512 ADPRHL2 337 456 1255 1717
+ADPRHL2_m36554557 ADPRHL2 1087 589 1204 1823
+ADPRHL2_m36554563 ADPRHL2 823 237 1247 1066
+ADPRHL2_m36554576 ADPRHL2 748 628 2075 2502
+ADPRHL2_m36554620 ADPRHL2 239 168 388 130
+ADPRHL2_p36554501 ADPRHL2 407 391 1071 1610
+ADPRHL2_p36554520 ADPRHL2 750 594 2176 1591
+ADPRHL2_p36554568 ADPRHL2 335 447 881 1510
+ADPRHL2_p36554580 ADPRHL2 578 527 1481 1293
+ADPRHL2_p36554606 ADPRHL2 175 138 84 355
+ADRA1A_m26722399 ADRA1A 110 130 597 857
+ADRA1A_m26722428 ADRA1A 0 0 108 322
+ADRA1A_m26722434 ADRA1A 716 734 1561 1900
+ADRA1A_m26722473 ADRA1A 552 327 1172 1094
+ADRA1A_p26722329 ADRA1A 1069 820 2273 2416
+ADRA1A_p26722406 ADRA1A 227 314 1002 1190
+ADRA1A_p26722412 ADRA1A 689 554 1599 1443
+ADRA1A_p26722419 ADRA1A 386 286 793 647
+ADRA1A_p26722438 ADRA1A 744 526 1152 1461
+ADRA1A_p26722465 ADRA1A 378 280 1518 394
+ADRA1B_m159343921 ADRA1B 46 138 311 193
+ADRA1B_m159343926 ADRA1B 358 462 1834 1238
+ADRA1B_m159343934 ADRA1B 509 676 1632 1313
+ADRA1B_m159343996 ADRA1B 509 295 1458 1358
+ADRA1B_m159344001 ADRA1B 224 174 1398 1182
+ADRA1B_m159344006 ADRA1B 341 125 345 760
+ADRA1B_m159344028 ADRA1B 731 297 1475 1304
+ADRA1B_p159343905 ADRA1B 279 165 70 585
+ADRA1B_p159343912 ADRA1B 782 825 1522 1899
+ADRA1B_p159343940 ADRA1B 731 705 2012 2117
+ADRB1_m115803922 ADRB1 157 126 616 620
+ADRB1_m115803930 ADRB1 300 124 716 632
+ADRB1_m115803938 ADRB1 588 662 1530 2374
+ADRB1_m115803996 ADRB1 439 290 1119 700
+ADRB1_m115804005 ADRB1 916 892 1255 1108
+ADRB1_m115804012 ADRB1 1474 1094 1733 1233
+ADRB1_m115804041 ADRB1 282 646 958 1752
+ADRB1_m115804047 ADRB1 434 307 611 563
+ADRB1_p115803878 ADRB1 298 647 2027 1533
+ADRB1_p115803909 ADRB1 393 357 1120 1694
+ADRB2_m148206406 ADRB2 564 485 1573 1390
+ADRB2_m148206447 ADRB2 562 463 1395 1143
+ADRB2_p148206408 ADRB2 731 425 2455 1785
+ADRB2_p148206418 ADRB2 302 232 732 632
+ADRB2_p148206432 ADRB2 318 630 939 939
+ADRB2_p148206450 ADRB2 414 494 1514 932
+ADRB2_p148206455 ADRB2 3368 2002 6329 7676
+ADRB2_p148206462 ADRB2 920 529 1751 2621
+ADRB2_p148206467 ADRB2 518 521 1030 1397
+ADRB2_p148206474 ADRB2 101 249 664 626
+ADRB3_m37823829 ADRB3 214 158 1095 887
+ADRB3_m37823842 ADRB3 97 0 0 242
+ADRB3_m37823867 ADRB3 171 134 398 767
+ADRB3_m37823894 ADRB3 827 1050 3426 3963
+ADRB3_p37823813 ADRB3 862 396 837 792
+ADRB3_p37823900 ADRB3 123 135 443 359
+ADRB3_p37823908 ADRB3 321 225 1162 1331
+ADRB3_p37823913 ADRB3 309 215 833 744
+ADRB3_p37823952 ADRB3 839 821 2409 2329
+ADRB3_p37823958 ADRB3 1511 550 2208 2013
+ADRBK1_m67034181 ADRBK1 253 494 3797 2735
+ADRBK1_m67034219 ADRBK1 755 641 1538 1746
+ADRBK1_m67034242 ADRBK1 995 681 2437 2655
+ADRBK1_m67034255 ADRBK1 399 556 1179 2293
+ADRBK1_p67034160 ADRBK1 693 404 1697 2000
+ADRBK1_p67034166 ADRBK1 864 683 2522 2840
+ADRBK1_p67034172 ADRBK1 899 1011 2344 2162
+ADRBK1_p67034193 ADRBK1 618 469 2599 2217
+ADRBK1_p67034199 ADRBK1 628 427 2345 2230
+ADRBK1_p67034261 ADRBK1 463 357 505 1103
+ADRBK2_m25961078 ADRBK2 215 236 789 926
+ADRBK2_m25961092 ADRBK2 1140 544 2086 3062
+ADRBK2_m25961108 ADRBK2 702 221 1434 1217
+ADRBK2_m26000349 ADRBK2 179 217 917 455
+ADRBK2_m26000370 ADRBK2 484 243 906 740
+ADRBK2_m26057580 ADRBK2 415 459 1917 1560
+ADRBK2_p25960997 ADRBK2 892 242 1961 1439
+ADRBK2_p25961098 ADRBK2 1384 463 1717 1821
+ADRBK2_p26040592 ADRBK2 290 342 410 1075
+ADRBK2_p26057601 ADRBK2 991 947 2744 3634
+ADRM1_m60878634 ADRM1 279 370 690 623
+ADRM1_m60878651 ADRM1 501 373 891 915
+ADRM1_m60878679 ADRM1 1078 907 2696 2532
+ADRM1_p60878615 ADRM1 325 474 280 783
+ADRM1_p60878642 ADRM1 64 70 112 789
+ADRM1_p60878671 ADRM1 286 76 488 546
+ADRM1_p60878682 ADRM1 688 402 1256 1923
+ADRM1_p60878687 ADRM1 138 180 680 90
+ADRM1_p60878704 ADRM1 186 378 576 565
+ADRM1_p60878730 ADRM1 423 358 622 1086
+AEBP1_m44144289 AEBP1 1334 1186 2582 3782
+AEBP1_m44144302 AEBP1 402 478 786 1505
+AEBP1_m44144319 AEBP1 675 505 775 1012
+AEBP1_m44144326 AEBP1 782 647 2562 2633
+AEBP1_m44144338 AEBP1 395 198 1099 513
+AEBP1_m44144355 AEBP1 357 1109 1602 1473
+AEBP1_p44144293 AEBP1 613 649 1571 2284
+AEBP1_p44144306 AEBP1 661 532 1463 891
+AEBP1_p44144347 AEBP1 707 560 1087 1375
+AEBP1_p44144359 AEBP1 524 496 916 1847
+AEBP2_m19615484 AEBP2 71 218 511 716
+AEBP2_m19615553 AEBP2 933 301 1372 1392
+AEBP2_m19615572 AEBP2 696 264 1156 1354
+AEBP2_m19615578 AEBP2 237 378 1301 1044
+AEBP2_p19615440 AEBP2 701 615 1392 1934
+AEBP2_p19615465 AEBP2 175 242 252 143
+AEBP2_p19615492 AEBP2 497 218 640 1437
+AEBP2_p19615498 AEBP2 637 511 990 1441
+AEBP2_p19615544 AEBP2 507 423 1167 1352
+AEBP2_p19615557 AEBP2 808 484 2226 1828
+AEN_m89169460 AEN 1093 875 2182 1989
+AEN_m89169478 AEN 940 749 2392 572
+AEN_m89169484 AEN 903 509 1547 1436
+AEN_m89169489 AEN 64 0 278 214
+AEN_m89169495 AEN 451 335 1322 685
+AEN_m89169500 AEN 462 320 1175 861
+AEN_m89169507 AEN 386 415 528 1381
+AEN_m89169544 AEN 365 387 800 689
+AEN_p89169516 AEN 983 602 2722 1738
+AEN_p89169534 AEN 701 600 2356 790
+AES_m3056311 AES 515 347 1414 2030
+AES_m3056337 AES 563 690 1812 2204
+AES_m3057678 AES 591 446 1183 1776
+AES_m3057717 AES 680 578 1487 2171
+AES_m3061159 AES 385 371 1586 1251
+AES_m3061215 AES 356 510 1912 1476
+AES_p3056318 AES 734 371 1264 1467
+AES_p3061179 AES 183 175 179 695
+AES_p3061186 AES 162 150 269 806
+AES_p3061195 AES 367 200 1323 339
+AFAP1L2_m116092987 AFAP1L2 598 262 1008 1705
+AFAP1L2_m116093045 AFAP1L2 482 477 1193 1342
+AFAP1L2_m116100394 AFAP1L2 453 557 1363 906
+AFAP1L2_m116100466 AFAP1L2 311 244 775 934
+AFAP1L2_p116092995 AFAP1L2 941 487 1418 1489
+AFAP1L2_p116100376 AFAP1L2 150 289 593 940
+AFAP1L2_p116100409 AFAP1L2 915 638 3685 2371
+AFAP1L2_p116100418 AFAP1L2 264 204 1090 1162
+AFAP1L2_p116100433 AFAP1L2 227 167 549 378
+AFAP1L2_p116164194 AFAP1L2 402 206 961 965
+AFF1_m87967374 AFF1 175 108 270 664
+AFF1_m87967382 AFF1 253 196 229 920
+AFF1_m87967432 AFF1 118 339 234 376
+AFF1_m87967920 AFF1 511 918 1733 1106
+AFF1_m87967978 AFF1 374 206 595 1219
+AFF1_p87967338 AFF1 422 361 1309 2027
+AFF1_p87967353 AFF1 1215 822 1522 2879
+AFF1_p87967869 AFF1 489 702 1911 1568
+AFF1_p87967890 AFF1 561 567 835 2301
+AFF1_p87967926 AFF1 539 580 2082 1397
+AFF2_m147891407 AFF2 242 211 431 1053
+AFF2_m147891412 AFF2 527 282 1329 1264
+AFF2_m147891420 AFF2 344 69 183 320
+AFF2_m147924509 AFF2 83 46 50 201
+AFF2_m147924918 AFF2 584 640 1261 4264
+AFF2_m147924923 AFF2 409 185 588 318
+AFF2_m147967463 AFF2 411 513 1474 1929
+AFF2_m147967470 AFF2 607 720 1417 2796
+AFF2_p147891422 AFF2 83 353 593 530
+AFF2_p147967406 AFF2 710 592 2176 2168
+AFF3_m100623802 AFF3 426 108 207 324
+AFF3_m100623914 AFF3 165 122 178 388
+AFF3_m100625275 AFF3 355 134 962 902
+AFF3_m100625319 AFF3 505 440 1515 1741
+AFF3_m100625326 AFF3 318 254 825 1101
+AFF3_m100625363 AFF3 789 429 801 533
+AFF3_p100623773 AFF3 1294 1028 2494 1487
+AFF3_p100623814 AFF3 646 605 968 2285
+AFF3_p100623867 AFF3 637 316 1053 1051
+AFF3_p100623873 AFF3 217 247 690 368
+AFF4_m132272813 AFF4 649 422 1198 2157
+AFF4_m132272826 AFF4 786 1234 3211 3711
+AFF4_m132272833 AFF4 929 1084 1731 2189
+AFF4_m132272841 AFF4 164 359 448 1402
+AFF4_m132272866 AFF4 816 826 2232 2605
+AFF4_p132272747 AFF4 359 64 115 579
+AFF4_p132272762 AFF4 382 267 1139 1059
+AFF4_p132272771 AFF4 375 781 1818 2643
+AFF4_p132272844 AFF4 408 530 1920 2421
+AFF4_p132272853 AFF4 515 381 1400 1598
+AFMID_m76183481 AFMID 477 551 978 1588
+AFMID_m76183493 AFMID 304 108 349 365
+AFMID_m76187074 AFMID 611 496 803 543
+AFMID_m76187079 AFMID 269 265 866 440
+AFMID_p76183445 AFMID 620 482 1487 1754
+AFMID_p76183450 AFMID 543 878 962 1761
+AFMID_p76183465 AFMID 108 337 504 414
+AFMID_p76183473 AFMID 261 241 1321 746
+AFMID_p76187060 AFMID 309 636 1105 1222
+AFMID_p76187082 AFMID 774 579 1274 1548
+AFTPH_m64778617 AFTPH 283 165 385 65
+AFTPH_m64778646 AFTPH 680 529 1310 2559
+AFTPH_m64778724 AFTPH 34 72 168 117
+AFTPH_m64778773 AFTPH 41 91 367 335
+AFTPH_m64778841 AFTPH 508 257 1696 967
+AFTPH_m64778905 AFTPH 315 199 981 1187
+AFTPH_p64778649 AFTPH 1173 845 2103 2885
+AFTPH_p64778713 AFTPH 1178 849 2447 1747
+AFTPH_p64778754 AFTPH 578 485 1208 1349
+AFTPH_p64778890 AFTPH 422 298 581 1149
+AGAP2_m58128438 AGAP2 556 505 1856 1455
+AGAP2_m58128444 AGAP2 1673 906 3114 3687
+AGAP2_m58128454 AGAP2 825 649 1423 1588
+AGAP2_m58129187 AGAP2 624 433 1675 1954
+AGAP2_m58129192 AGAP2 541 409 1625 662
+AGAP2_p58128423 AGAP2 287 288 635 725
+AGAP2_p58129143 AGAP2 515 282 1256 456
+AGAP2_p58129148 AGAP2 519 670 986 1154
+AGAP2_p58129153 AGAP2 208 115 403 489
+AGAP2_p58129171 AGAP2 346 511 2100 2182
+AGAP3_m150784003 AGAP3 944 631 1925 1942
+AGAP3_p150783818 AGAP3 264 287 1479 1311
+AGAP3_p150783825 AGAP3 222 358 1523 1076
+AGAP3_p150783857 AGAP3 904 585 2134 2790
+AGAP3_p150783866 AGAP3 240 132 492 750
+AGAP3_p150783903 AGAP3 472 382 1243 1565
+AGAP3_p150783915 AGAP3 570 405 594 1737
+AGAP3_p150783972 AGAP3 249 208 529 1305
+AGAP3_p150784007 AGAP3 481 358 1327 2561
+AGAP3_p150784015 AGAP3 331 379 1244 1284
+AGBL5_m27275887 AGBL5 436 339 487 337
+AGBL5_m27275950 AGBL5 241 158 324 482
+AGBL5_m27275975 AGBL5 530 525 1234 1582
+AGBL5_m27276001 AGBL5 425 312 588 976
+AGBL5_m27276006 AGBL5 771 785 1013 1977
+AGBL5_p27275820 AGBL5 288 232 356 746
+AGBL5_p27275854 AGBL5 202 467 776 2155
+AGBL5_p27275870 AGBL5 466 308 625 990
+AGBL5_p27275876 AGBL5 300 355 689 799
+AGBL5_p27275898 AGBL5 754 1109 1690 2331
+AGFG1_m228337138 AGFG1 714 564 2746 1557
+AGFG1_m228337178 AGFG1 374 575 1247 1529
+AGFG1_m228337201 AGFG1 635 496 1007 1334
+AGFG1_m228337208 AGFG1 457 440 879 1340
+AGFG1_m228337217 AGFG1 229 348 573 750
+AGFG1_m228337248 AGFG1 669 378 1071 587
+AGFG1_m228337276 AGFG1 1621 1273 2485 2620
+AGFG1_p228337142 AGFG1 0 24 0 137
+AGFG1_p228337168 AGFG1 454 376 780 1240
+AGFG1_p228337221 AGFG1 306 241 1131 1122
+AGL_m100327112 AGL 777 539 1842 2115
+AGL_m100327128 AGL 83 140 505 640
+AGL_m100327135 AGL 151 67 664 807
+AGL_m100327186 AGL 94 90 635 232
+AGL_m100327263 AGL 516 261 650 368
+AGL_p100327060 AGL 497 260 523 675
+AGL_p100327074 AGL 413 555 1032 899
+AGL_p100327114 AGL 32 83 380 54
+AGL_p100327219 AGL 134 162 66 137
+AGL_p100327246 AGL 315 143 320 626
+AGPAT3_m45379563 AGPAT3 179 141 81 288
+AGPAT3_m45379570 AGPAT3 87 130 303 281
+AGPAT3_m45379578 AGPAT3 69 88 328 395
+AGPAT3_m45379590 AGPAT3 819 918 2207 1744
+AGPAT3_m45379606 AGPAT3 256 166 527 358
+AGPAT3_p45379552 AGPAT3 710 651 2228 2263
+AGPAT3_p45379592 AGPAT3 734 254 476 439
+AGPAT3_p45379613 AGPAT3 407 172 740 481
+AGPAT3_p45379618 AGPAT3 40 396 699 1463
+AGPAT3_p45379648 AGPAT3 701 370 934 719
+AGPAT5_m6566202 AGPAT5 195 321 307 227
+AGPAT5_m6566212 AGPAT5 1668 1381 3410 4278
+AGPAT5_m6566223 AGPAT5 782 1145 2701 2379
+AGPAT5_m6566233 AGPAT5 2271 2181 4502 4135
+AGPAT5_m6566240 AGPAT5 546 898 1383 1661
+AGPAT5_m6566254 AGPAT5 520 268 586 1373
+AGPAT5_m6566307 AGPAT5 196 141 369 188
+AGPAT5_p6566182 AGPAT5 329 233 790 1033
+AGPAT5_p6566257 AGPAT5 941 738 1815 1921
+AGPAT5_p6566262 AGPAT5 474 274 1506 1191
+AGTPBP1_m88296213 AGTPBP1 531 492 2269 2580
+AGTPBP1_m88296222 AGTPBP1 1138 509 1909 2637
+AGTPBP1_m88307605 AGTPBP1 495 251 796 824
+AGTPBP1_m88307687 AGTPBP1 1353 700 2269 2760
+AGTPBP1_m88307696 AGTPBP1 0 204 694 669
+AGTPBP1_p88296203 AGTPBP1 298 192 727 1188
+AGTPBP1_p88307644 AGTPBP1 206 189 435 608
+AGTPBP1_p88307675 AGTPBP1 800 646 1441 2138
+AGTPBP1_p88307700 AGTPBP1 107 67 64 1054
+AGTPBP1_p88307705 AGTPBP1 446 253 716 903
+AHCTF1_m247067252 AHCTF1 134 170 672 60
+AHCTF1_m247068844 AHCTF1 753 595 2763 1411
+AHCTF1_m247068867 AHCTF1 509 275 380 835
+AHCTF1_m247068886 AHCTF1 745 497 1328 638
+AHCTF1_m247068945 AHCTF1 461 178 973 1432
+AHCTF1_m247070906 AHCTF1 734 906 553 339
+AHCTF1_m247070995 AHCTF1 978 617 508 282
+AHCTF1_m247094617 AHCTF1 575 372 858 1120
+AHCTF1_p247076572 AHCTF1 375 417 1749 1088
+AHCTF1_p247079429 AHCTF1 409 507 1166 1318
+AHCY_m32883210 AHCY 205 370 362 240
+AHCY_m32883247 AHCY 777 619 179 176
+AHCY_m32883267 AHCY 537 378 1147 1029
+AHCY_m32883301 AHCY 267 232 530 374
+AHCY_m32883330 AHCY 1367 1259 3863 3387
+AHCY_p32883227 AHCY 729 229 1023 611
+AHCY_p32883238 AHCY 42 123 974 791
+AHCY_p32883253 AHCY 443 495 376 33
+AHCY_p32883304 AHCY 1106 794 3402 3472
+AHCY_p32883309 AHCY 717 497 169 185
+AHNAK2_m105423801 AHNAK2 827 932 2364 2698
+AHNAK2_m105423809 AHNAK2 275 265 776 1124
+AHNAK2_m105423822 AHNAK2 215 414 1125 1162
+AHNAK2_m105423829 AHNAK2 502 495 890 704
+AHNAK2_m105423836 AHNAK2 200 460 2170 1886
+AHNAK2_m105444536 AHNAK2 260 256 1122 1064
+AHNAK2_m105444541 AHNAK2 518 374 1342 1589
+AHNAK2_m105444555 AHNAK2 343 156 257 1290
+AHNAK2_p105423957 AHNAK2 460 311 497 1143
+AHNAK2_p105423983 AHNAK2 247 219 1549 972
+AHNAK_m62303488 AHNAK 272 284 1238 1124
+AHNAK_m62303507 AHNAK 79 133 464 34
+AHNAK_m62303523 AHNAK 122 168 238 534
+AHNAK_m62303528 AHNAK 181 449 1074 1467
+AHNAK_m62303548 AHNAK 591 552 1143 573
+AHNAK_m62303560 AHNAK 479 540 1629 2630
+AHNAK_p62303470 AHNAK 258 412 1397 1743
+AHNAK_p62303477 AHNAK 446 282 879 831
+AHNAK_p62303510 AHNAK 322 254 948 862
+AHNAK_p62303551 AHNAK 35 23 186 55
+AHRR_m344006 AHRR 235 92 752 841
+AHRR_m344069 AHRR 283 210 337 610
+AHRR_m353878 AHRR 1 47 0 110
+AHRR_m353892 AHRR 239 85 458 728
+AHRR_m353898 AHRR 382 96 316 720
+AHRR_p344008 AHRR 171 125 2480 2626
+AHRR_p344030 AHRR 501 503 1767 803
+AHRR_p344036 AHRR 230 342 600 114
+AHRR_p344042 AHRR 837 296 1327 1652
diff -r 93f268840b0c -r 9cd937788131 test-data/out.count.R
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/out.count.R Wed Apr 04 11:03:44 2018 -0400
@@ -0,0 +1,5 @@
+Sweave("output_countsummary.Rnw");
+library(tools);
+
+texi2dvi("output_countsummary.tex",pdf=TRUE);
+
diff -r 93f268840b0c -r 9cd937788131 test-data/out.count.Rnw
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/out.count.Rnw Wed Apr 04 11:03:44 2018 -0400
@@ -0,0 +1,237 @@
+% This is a template file for Sweave used in MAGeCK
+% Author: Wei Li, Shirley Liu lab
+% Do not modify lines beginning with "#__".
+\documentclass{article}
+
+\usepackage{amsmath}
+\usepackage{amscd}
+\usepackage[tableposition=top]{caption}
+\usepackage{ifthen}
+\usepackage{fullpage}
+\usepackage[utf8]{inputenc}
+% \usepackage{longtable}
+
+\begin{document}
+\setkeys{Gin}{width=0.9\textwidth}
+
+\title{MAGeCK Count Report}
+\author{Wei Li}
+
+\maketitle
+
+
+\tableofcontents
+
+\section{Summary}
+
+%Function definition
+<>=
+genreporttable<-function(filelist,labellist,reads,mappedreads){
+ xtb=data.frame(Label=labellist,Reads=reads,MappedReads=mappedreads,MappedPercentage=mappedreads/reads);
+ colnames(xtb)=c("Label","Reads","Mapped","Percentage");
+ return (xtb);
+}
+genreporttable2<-function(filelist,labellist,sgrnas,zerocounts,gini){
+ xtb=data.frame(Label=labellist,TotalsgRNAs=sgrnas,ZeroCounts=zerocounts,GiniIndex=gini);
+ colnames(xtb)=c("Label","TotalsgRNA","ZeroCounts","GiniIndex");
+ return (xtb);
+}
+genreporttable3<-function(filelist,labellist){
+ xtb=data.frame(File=filelist,Label=labellist);
+ colnames(xtb)=c("File","Label");
+ return (xtb);
+}
+
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F");
+
+
+
+genboxplot<-function(filename,...){
+ #slmed=read.table(filename,header=T)
+ slmed=read.table(filename,header=T)
+ slmat=as.matrix(slmed[,c(-1,-2)])
+ slmat_log=log2(slmat+1)
+
+ boxplot(slmat_log,pch='.',las=2,ylab='log2(read counts)',cex.axis=0.8,...)
+}
+
+
+genhistplot<-function(filename,isfile=T,...){
+ if(isfile){
+ slmed=read.table(filename,header=T)
+ }else{
+ slmed=filename;
+ }
+ tabsmat=as.matrix(log2(slmed[,c(-1,-2)]+1))
+ colnames(tabsmat)=colnames(slmed)[c(-1,-2)]
+ samplecol=colors[((1:ncol(tabsmat)) %% length(colors)) ]
+ if(ncol(tabsmat)>=1){
+ histlist=lapply(1:ncol(tabsmat),function(X){ return (hist(tabsmat[,X],plot=F,breaks=40)) })
+ xrange=range(unlist(lapply(histlist,function(X){X$mids})))
+ yrange=range(unlist(lapply(histlist,function(X){X$counts})))
+ hst1=histlist[[1]]
+ plot(hst1$mids,hst1$counts,type='b',pch=20,xlim=c(0,xrange[2]*1.2),ylim=c(0,yrange[2]*1.2),xlab='log2(counts)',ylab='Frequency',main='Distribution of read counts',col = samplecol[1], ... )
+ }
+ if(ncol(tabsmat)>=2){
+ for(i in 2:ncol(tabsmat)){
+ hstn=histlist[[i]]
+ lines(hstn$mids,hstn$counts,type='b',pch=20,col=samplecol[i])
+ }
+ }
+ legend('topright',colnames(tabsmat),pch=20,lwd=1,col=samplecol)
+}
+
+
+
+genclustering<-function(filename,...){
+ #slmed=read.table(filename,header=T)
+ slmed=read.table(filename,header=T)
+ slmat=as.matrix(slmed[,c(-1,-2)])
+ slmat_log=log2(slmat+1)
+
+ result=tryCatch({
+ library(gplots);
+ heatmap.2(cor(slmat_log),trace = 'none',density.info = 'none',cexRow = 0.8,cexCol = 0.8,offsetRow = -0.2,offsetCol = -0.2)
+ }, error=function(e){
+ heatmap(cor(slmat_log),scale='none',cexRow = 0.8,cexCol = 0.8,cex.axis=0.8,...)
+ });
+}
+
+ctfit_tx=0;
+
+
+panel.plot<-function(x,y,textnames=names(x),...){
+ par(new=TRUE)
+ m<-cbind(x,y)
+ plot(m,pch=20,xlim = range(x)*1.1,ylim=range(y)*1.1,...)
+ text(x,y,textnames,...)
+}
+
+
+genpcaplot<-function(filename,...){
+ #slmed=read.table(filename,header=T)
+ slmed=read.table(filename,header=T)
+ slmat=as.matrix(slmed[,c(-1,-2)])
+ slmat_log=log2(slmat+1)
+ ctfit_tx<<-prcomp(t(slmat_log),center=TRUE)
+
+ # par(mfrow=c(2,1));
+ samplecol=colors[((1:ncol(slmat)) %% length(colors)) ]
+ # first 2 PCA
+ #plot(ctfit_tx$x[,1],ctfit_tx$x[,2],xlab='PC1',ylab='PC2',main='First 2 PCs',col=samplecol,xlim=1.1*range(ctfit_tx$x[,1]),ylim=1.1*range(ctfit_tx$x[,2]));
+ #text(ctfit_tx$x[,1],ctfit_tx$x[,2],rownames(ctfit_tx$x),col=samplecol);
+ # par(mfrow=c(1,1));
+ if(length(samplecol)>2){
+ pairs(ctfit_tx$x[,1:3],panel=panel.plot,textnames=rownames(ctfit_tx$x),main='First 3 principle components',col=samplecol)
+ }else{
+ if(length(samplecol)>1){
+ pairs(ctfit_tx$x[,1:2],panel=panel.plot,textnames=rownames(ctfit_tx$x),main='First 2 principle components',col=samplecol)
+ }
+ }
+
+
+}
+
+genpcavar<-function(){
+ # % variance
+ varpca=ctfit_tx$sdev^2
+ varpca=varpca/sum(varpca)*100;
+ if(length(varpca)>10){
+ varpca=varpca[1:10];
+ }
+ plot(varpca,type='b',lwd=2,pch=20,xlab='PCs',ylab='% Variance explained');
+}
+
+@
+
+%__FILE_SUMMARY__
+
+The statistics of comparisons are listed in Table 1 and Table 2.
+The corresponding fastq files in each row are listed in Table 3.
+
+<>=
+library(xtable)
+filelist=c("input_0.gz");
+labellist=c("test1_fastq_gz");
+reads=c(2500);
+mappedreads=c(1453);
+totalsgrnas=c(2550);
+zerocounts=c(1276);
+giniindex=c(0.5266899931488773);
+
+cptable=genreporttable(filelist,labellist,reads,mappedreads);
+print(xtable(cptable, caption = "Summary of comparisons", label = "tab:one",
+ digits = c(0, 0, 0, 0,2),
+ align=c('c', 'c','c', 'c', 'c'),
+ table.placement = "tbp",
+ caption.placement = "top"))
+@
+
+<>=
+library(xtable)
+cptable=genreporttable2(filelist,labellist,totalsgrnas,zerocounts,giniindex);
+print(xtable(cptable, caption = "Summary of comparisons", label = "tab:two",
+ digits = c(0, 0,0, 0,2),
+ align=c('c', 'c','c', 'c', 'c'),
+ table.placement = "tbp",
+ caption.placement = "top"))
+@
+
+
+
+
+
+<>=
+library(xtable)
+cptable=genreporttable3(filelist,labellist);
+print(xtable(cptable, caption = "Summary of samples", label = "tab:three",
+ digits = c(0,0, 0),
+ align=c('c', 'p{9cm}', 'c'),
+ table.placement = "tbp",
+ caption.placement = "top"))
+@
+
+
+
+
+The meanings of the columns are as follows.
+
+\begin{itemize}
+\item \textbf{Row}: The row number in the table;
+\item \textbf{File}: The filename of fastq file;
+\item \textbf{Label}: Assigned label;
+\item \textbf{Reads}: The total read count in the fastq file;
+\item \textbf{Mapped}: Reads that can be mapped to gRNA library;
+\item \textbf{Percentage}: The percentage of mapped reads;
+\item \textbf{TotalsgRNAs}: The number of sgRNAs in the library;
+\item \textbf{ZeroCounts}: The number of sgRNA with 0 read counts;
+\item \textbf{GiniIndex}: The Gini Index of the read count distribution. Gini index can be used to measure the evenness of the read counts, and a smaller value means a more even distribution of the read counts.
+\end{itemize}
+
+
+
+\newpage\section{Normalized read count distribution of all samples}
+The following figure shows the distribution of median-normalized read counts in all samples.
+
+
+<>=
+genboxplot("output.count_normalized.txt");
+@
+
+The following figure shows the histogram of median-normalized read counts in all samples.
+
+
+<>=
+genhistplot("output.count_normalized.txt");
+@
+
+%__INDIVIDUAL_PAGE__
+
+
+
+\end{document}
+
diff -r 93f268840b0c -r 9cd937788131 test-data/out.count.bam.txt
--- a/test-data/out.count.bam.txt Sat Feb 17 10:41:41 2018 -0500
+++ b/test-data/out.count.bam.txt Wed Apr 04 11:03:44 2018 -0400
@@ -1,4 +1,4 @@
-sgRNA Gene test1.bam
+sgRNA Gene test1_bam
s_10007 CCNA1 0
s_10008 CCNA1 0
s_10027 CCNC 0
diff -r 93f268840b0c -r 9cd937788131 test-data/out.count.fastq.txt
--- a/test-data/out.count.fastq.txt Sat Feb 17 10:41:41 2018 -0500
+++ b/test-data/out.count.fastq.txt Wed Apr 04 11:03:44 2018 -0400
@@ -1,4 +1,4 @@
-sgRNA Gene test1.fastq.gz
+sgRNA Gene test1_fastq_gz
s_47512 RNF111 1
s_24835 HCFC1R1 1
s_14784 CYP4B1 4
diff -r 93f268840b0c -r 9cd937788131 test-data/out.count.log.txt
--- a/test-data/out.count.log.txt Sat Feb 17 10:41:41 2018 -0500
+++ b/test-data/out.count.log.txt Wed Apr 04 11:03:44 2018 -0400
@@ -1,46 +1,43 @@
-INFO @ Wed, 14 Feb 2018 01:52:58: Parameters: /home/maria/miniconda3/envs/mulled-v1-0142cfe25b04f0c1d6899e250fb2f311b2d84778259938a0f6bd1d2ee743fa71/bin/mageck count -l /tmp/tmpqZ84Xc/files/000/dataset_7.dat --fastq input.gz -n output --pdf-report --keep-tmp --unmapped-to-file --norm-method median --sgrna-len 20
-INFO @ Wed, 14 Feb 2018 01:52:58: Welcome to MAGeCK v0.5.7. Command: count
-INFO @ Wed, 14 Feb 2018 01:52:58: Loading 2550 predefined sgRNAs.
-WARNING @ Wed, 14 Feb 2018 01:52:58: There are 0 sgRNAs with duplicated sequences.
-INFO @ Wed, 14 Feb 2018 01:52:58: Parsing FASTQ file input.gz...
-INFO @ Wed, 14 Feb 2018 01:52:58: Determining the trim-5 length of FASTQ file input.gz...
-INFO @ Wed, 14 Feb 2018 01:52:58: Possible gRNA lengths:20
-INFO @ Wed, 14 Feb 2018 01:52:58: Processing 0M reads ...
-INFO @ Wed, 14 Feb 2018 01:52:58: Read length:30
-INFO @ Wed, 14 Feb 2018 01:52:58: Total tested reads: 2500, mapped: 1453(0.5812)
-INFO @ Wed, 14 Feb 2018 01:52:58: --trim-5 test data: (trim_length reads fraction)
-INFO @ Wed, 14 Feb 2018 01:52:58: 0 1453 1.0
-INFO @ Wed, 14 Feb 2018 01:52:58: Auto determination of trim5 results: 0
-INFO @ Wed, 14 Feb 2018 01:52:58: Possible gRNA lengths:20
-INFO @ Wed, 14 Feb 2018 01:52:58: Processing 0M reads ..
-INFO @ Wed, 14 Feb 2018 01:52:58: Total: 2500.
-INFO @ Wed, 14 Feb 2018 01:52:58: Mapped: 1453.
-DEBUG @ Wed, 14 Feb 2018 01:52:58: Initial (total) size factor: 1.0
-DEBUG @ Wed, 14 Feb 2018 01:52:58: Median factor: 2.0
-INFO @ Wed, 14 Feb 2018 01:52:58: Final size factor: 2.0
-INFO @ Wed, 14 Feb 2018 01:52:58: Summary of file input.gz:
-INFO @ Wed, 14 Feb 2018 01:52:58: label sample1
-INFO @ Wed, 14 Feb 2018 01:52:58: reads 2500
-INFO @ Wed, 14 Feb 2018 01:52:58: mappedreads 1453
-INFO @ Wed, 14 Feb 2018 01:52:58: totalsgrnas 2550
-INFO @ Wed, 14 Feb 2018 01:52:58: zerosgrnas 1276
-INFO @ Wed, 14 Feb 2018 01:52:58: giniindex 0.5266899931488773
-INFO @ Wed, 14 Feb 2018 01:52:58: Loading Rnw template file: /home/maria/miniconda3/envs/mulled-v1-0142cfe25b04f0c1d6899e250fb2f311b2d84778259938a0f6bd1d2ee743fa71/lib/python3.6/site-packages/mageck/fastq_template.Rnw.
-DEBUG @ Wed, 14 Feb 2018 01:52:58: Setting up the visualization module...
-INFO @ Wed, 14 Feb 2018 01:52:58: Running command: cd ./; Rscript output_countsummary.R
-INFO @ Wed, 14 Feb 2018 01:52:58: Command message:
-INFO @ Wed, 14 Feb 2018 01:52:58: Writing to file output_countsummary.tex
-INFO @ Wed, 14 Feb 2018 01:52:58: Processing code chunks with options ...
-INFO @ Wed, 14 Feb 2018 01:52:58: 1 : keep.source term verbatim (label = funcdef, output_countsummary.Rnw:28)
-INFO @ Wed, 14 Feb 2018 01:52:58: 2 : keep.source term tex (label = tab1, output_countsummary.Rnw:156)
-INFO @ Wed, 14 Feb 2018 01:52:58: 3 : keep.source term tex (label = tab2, output_countsummary.Rnw:174)
-INFO @ Wed, 14 Feb 2018 01:52:58: 4 : keep.source term tex (label = tab3, output_countsummary.Rnw:188)
-INFO @ Wed, 14 Feb 2018 01:52:58: 5 : keep.source term verbatim pdf (output_countsummary.Rnw:221)
-INFO @ Wed, 14 Feb 2018 01:52:58: 6 : keep.source term verbatim pdf (output_countsummary.Rnw:228)
-INFO @ Wed, 14 Feb 2018 01:52:58:
-INFO @ Wed, 14 Feb 2018 01:52:58: You can now run (pdf)latex on ‘output_countsummary.tex’
-INFO @ Wed, 14 Feb 2018 01:52:58: Error in texi2dvi("output_countsummary.tex", pdf = TRUE) :
-INFO @ Wed, 14 Feb 2018 01:52:58: pdflatex is not available
-INFO @ Wed, 14 Feb 2018 01:52:58: Execution halted
-INFO @ Wed, 14 Feb 2018 01:52:58:
-INFO @ Wed, 14 Feb 2018 01:52:58: End command message.
+INFO @ Sun, 25 Mar 2018 15:51:06: Parameters: /Users/doylemaria/miniconda3/envs/mulled-v1-5ed9647f14e9d3e99564d31bed2eb19cd32ee8b9da66a89bea59b64a8983b1d6/bin/mageck count -l /private/var/folders/zn/m_qvr9zd7tq0wdtsbq255f8xypj_zg/T/tmp0EKzNL/files/000/dataset_2.dat --fastq input_0.gz --sample-label test1_fastq_gz -n output --pdf-report --keep-tmp --unmapped-to-file
+INFO @ Sun, 25 Mar 2018 15:51:06: Welcome to MAGeCK v0.5.7. Command: count
+INFO @ Sun, 25 Mar 2018 15:51:06: Loading 2550 predefined sgRNAs.
+WARNING @ Sun, 25 Mar 2018 15:51:06: There are 0 sgRNAs with duplicated sequences.
+INFO @ Sun, 25 Mar 2018 15:51:06: Parsing FASTQ file input_0.gz...
+INFO @ Sun, 25 Mar 2018 15:51:06: Determining the trim-5 length of FASTQ file input_0.gz...
+INFO @ Sun, 25 Mar 2018 15:51:06: Possible gRNA lengths:20
+INFO @ Sun, 25 Mar 2018 15:51:06: Processing 0M reads ...
+INFO @ Sun, 25 Mar 2018 15:51:06: Read length:30
+INFO @ Sun, 25 Mar 2018 15:51:06: Total tested reads: 2500, mapped: 1453(0.5812)
+INFO @ Sun, 25 Mar 2018 15:51:06: --trim-5 test data: (trim_length reads fraction)
+INFO @ Sun, 25 Mar 2018 15:51:06: 0 1453 1.0
+INFO @ Sun, 25 Mar 2018 15:51:06: Auto determination of trim5 results: 0
+INFO @ Sun, 25 Mar 2018 15:51:06: Possible gRNA lengths:20
+INFO @ Sun, 25 Mar 2018 15:51:06: Processing 0M reads ..
+INFO @ Sun, 25 Mar 2018 15:51:06: Total: 2500.
+INFO @ Sun, 25 Mar 2018 15:51:06: Mapped: 1453.
+DEBUG @ Sun, 25 Mar 2018 15:51:06: Initial (total) size factor: 1.0
+DEBUG @ Sun, 25 Mar 2018 15:51:06: Median factor: 2.0
+INFO @ Sun, 25 Mar 2018 15:51:06: Final size factor: 2.0
+INFO @ Sun, 25 Mar 2018 15:51:06: Summary of file input_0.gz:
+INFO @ Sun, 25 Mar 2018 15:51:06: label test1_fastq_gz
+INFO @ Sun, 25 Mar 2018 15:51:06: reads 2500
+INFO @ Sun, 25 Mar 2018 15:51:06: mappedreads 1453
+INFO @ Sun, 25 Mar 2018 15:51:06: totalsgrnas 2550
+INFO @ Sun, 25 Mar 2018 15:51:06: zerosgrnas 1276
+INFO @ Sun, 25 Mar 2018 15:51:06: giniindex 0.5266899931488773
+INFO @ Sun, 25 Mar 2018 15:51:06: Loading Rnw template file: /Users/doylemaria/miniconda3/envs/mulled-v1-5ed9647f14e9d3e99564d31bed2eb19cd32ee8b9da66a89bea59b64a8983b1d6/lib/python3.6/site-packages/mageck/fastq_template.Rnw.
+DEBUG @ Sun, 25 Mar 2018 15:51:06: Setting up the visualization module...
+INFO @ Sun, 25 Mar 2018 15:51:06: Running command: cd ./; Rscript output_countsummary.R
+INFO @ Sun, 25 Mar 2018 15:51:11: Command message:
+INFO @ Sun, 25 Mar 2018 15:51:11: Writing to file output_countsummary.tex
+INFO @ Sun, 25 Mar 2018 15:51:11: Processing code chunks with options ...
+INFO @ Sun, 25 Mar 2018 15:51:11: 1 : keep.source term verbatim (label = funcdef, output_countsummary.Rnw:28)
+INFO @ Sun, 25 Mar 2018 15:51:11: 2 : keep.source term tex (label = tab1, output_countsummary.Rnw:156)
+INFO @ Sun, 25 Mar 2018 15:51:11: 3 : keep.source term tex (label = tab2, output_countsummary.Rnw:174)
+INFO @ Sun, 25 Mar 2018 15:51:11: 4 : keep.source term tex (label = tab3, output_countsummary.Rnw:188)
+INFO @ Sun, 25 Mar 2018 15:51:11: 5 : keep.source term verbatim pdf (output_countsummary.Rnw:221)
+INFO @ Sun, 25 Mar 2018 15:51:11: 6 : keep.source term verbatim pdf (output_countsummary.Rnw:228)
+INFO @ Sun, 25 Mar 2018 15:51:11:
+INFO @ Sun, 25 Mar 2018 15:51:11: You can now run (pdf)latex on ‘output_countsummary.tex’
+INFO @ Sun, 25 Mar 2018 15:51:11:
+INFO @ Sun, 25 Mar 2018 15:51:11: End command message.
diff -r 93f268840b0c -r 9cd937788131 test-data/out.count.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/out.count.txt Wed Apr 04 11:03:44 2018 -0400
@@ -0,0 +1,2551 @@
+sgRNA Gene test1_fastq_gz
+s_47512 RNF111 1
+s_24835 HCFC1R1 1
+s_14784 CYP4B1 4
+s_51146 SLC18A1 1
+s_58960 TRIM5 1
+s_48256 RPRD2 1
+s_30297 KRTAP5-5 1
+s_14555 CYB5B 1
+s_39959 PAAF1 1
+s_45293 PUF60 1
+s_49358 SCN8A 1
+s_64995 ZYG11A 1
+s_4029 ASTE1 1
+s_45554 R3HDML 1
+s_34264 MMRN1 1
+s_37459 NOL6 1
+s_23990 GPX7 1
+s_20268 FANCC 1
+s_14157 CTLA4 1
+s_36773 NEURL4 18
+s_18804 ETFB 1
+s_782 ACSS1 1
+s_18272 ENPP2 1
+s_46620 RCN1 1
+s_55436 TAS2R3 1
+s_57947 TMPRSS2 1
+s_6438 C14orf159 1
+s_33846 MGST2 1
+s_16328 DNAH6 1
+s_17875 EIF4G1 1
+s_2305 ANAPC11 1
+s_2500 ANKRD2 1
+s_82 AARSD1 1
+s_55329 TAL1 1
+s_57926 TMPRSS11E 8
+s_38414 NUP98 4
+s_50044 SERPINF1 1
+s_9257 CASR 1
+s_63396 ZNF182 1
+s_56478 THBS3 1
+s_17191 DYRK1A 1
+s_11988 CIR1 1
+s_43313 PPARD 1
+s_44681 PSMA4 1
+s_10387 CD320 1
+s_64869 ZPBP 1
+s_54385 STK17B 1
+s_25423 HIST1H4D 1
+s_54172 ST8SIA4 9
+s_1161 ADCY10 1
+s_29184 KIAA0913 1
+s_42977 POLD3 1
+s_49449 SCUBE1 1
+s_24181 GRM4 1
+s_52507 SMARCA5 1
+s_28674 KCNJ10 1
+s_61074 VAMP2 4
+s_3954 ASIC2 1
+s_2385 ANK1 1
+s_18397 EPDR1 1
+s_18377 EPB41L4B 1
+s_34580 MRAP2 1
+s_48676 RUFY3 10
+s_691 ACP1 1
+s_30460 LAMP2 1
+s_42637 PLRG1 1
+s_12695 CNOT6 1
+s_33316 MECOM 2
+s_35081 MSRB2 1
+s_58512 TPD52L2 1
+s_19912 FAM22F 1
+s_45517 QSOX2 1
+s_56705 TINAG 1
+s_10946 CDKL5 1
+s_57473 TMEM211 2
+s_57657 TMEM44 1
+s_43200 POT1 1
+s_19436 FAM135A 1
+s_184 ABCB9 1
+s_30171 KRT84 1
+s_44758 PSMC3IP 1
+s_48313 RPS3 1
+s_58142 TNFSF12 6
+s_59718 TTLL6 7
+s_9725 CCDC43 1
+s_5135 BCKDHA 1
+s_36539 NDUFC2 1
+s_27251 IL27RA 1
+s_48939 SAMD10 1
+s_27343 IL5RA 1
+s_28386 KANK2 1
+s_27610 INSRR 1
+s_2769 AOC3 2
+s_58632 TRA2B 12
+s_6674 C16orf86 1
+s_22902 GJD4 1
+s_48278 RPS15A 1
+s_61998 WIPF2 1
+s_4937 BAIAP3 2
+s_54471 STOML1 2
+s_19157 FABP12 1
+s_5434 BIN1 2
+s_42042 PIP5K1A 1
+s_7794 C3orf18 1
+s_54846 SVIL 1
+s_62273 XPA 1
+s_45859 RACGAP1 1
+s_53626 SPOCK3 1
+s_43295 PPAP2C 7
+s_11788 CHRDL1 2
+s_50636 SHQ1 1
+s_16705 DPF1 1
+s_39741 OTOF 1
+s_27505 INHBE 1
+s_707 ACPL2 1
+s_15418 DDX3Y 6
+s_56018 TEAD4 1
+s_44367 PRR12 1
+s_25875 HOXB5 1
+s_49360 SCN9A 1
+s_16244 DMPK 1
+s_3909 ASCC2 1
+s_55088 SYT6 1
+s_54311 STAU1 1
+s_53890 SRP72 1
+s_11035 CDX1 1
+s_18178 EMR3 2
+s_16084 DLD 1
+s_47207 RHOBTB1 1
+s_40267 PARK2 6
+s_43104 POLR3B 1
+s_2200 AMDHD2 1
+s_12738 CNRIP1 1
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+s_49497 SDCBP2 3
+s_16874 DRP2 1
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+s_20540 FBXO30 1
+s_64380 ZNF646 1
+s_50366 SH2B1 1
+s_2548 ANKRD33B 1
+s_41183 PDXP 1
+s_16315 DNAH12 1
+s_19996 FAM49B 1
+s_30751 LDLRAD3 1
+s_36960 NGEF 1
+s_39015 OR2A2 1
+s_26302 HSPB2 1
+s_64297 ZNF611 5
+s_730 ACSBG1 1
+s_50271 SFXN4 1
+s_8592 CA6 2
+s_13683 CRMP1 1
+s_51103 SLC16A7 1
+s_63785 ZNF384 1
+s_16339 DNAH9 1
+s_55936 TCTEX1D1 1
+s_14497 CXorf40A 1
+s_1123 ADAT1 1
+s_41304 PERP 1
+s_18719 ESAM 1
+s_35118 MSX2 1
+s_30128 KRT6A 1
+s_402 ABTB1 1
+s_32578 MAP1LC3A 1
+s_45063 PTMA 1
+s_43551 PPP1R14D 1
+s_2538 ANKRD32 1
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+s_29076 KIAA0101 1
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+s_2348 ANGPT2 1
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+s_34330 MOB4 1
+s_49331 SCN2B 1
+s_54905 SYDE1 1
+s_39101 OR2T1 1
+s_36623 NEDD4L 1
+s_40500 PCDH15 2
+s_10660 CDC42SE2 1
+s_30867 LGALS13 1
+s_24322 GSTK1 2
+s_59167 TRPC1 1
+s_57440 TMEM201 1
+s_50539 SHC1 1
+s_37087 NIT1 1
+s_56345 TGFB2 1
+s_55388 TARM1 1
+s_1224 ADD2 1
+s_5256 BCOR 2
+s_51731 SLC35B3 1
+s_12987 COL6A6 1
+s_56745 TJP3 1
+s_19340 FAM120AOS 1
+s_53904 SRPR 1
+s_1588 AGXT 1
+s_46157 RASA3 1
+s_19166 FABP3 7
+s_22330 GATM 1
+s_10731 CDH13 1
+s_2329 ANAPC5 1
+s_46045 RANGAP1 1
+s_54814 SUV39H2 1
+s_56169 TEX14 1
+s_3433 ARHGEF26 1
+s_48032 RP4-811H24.6 1
+s_51930 SLC41A3 1
+s_63893 ZNF433 1
+s_46996 RGCC 1
+s_13863 CSF3R 1
+s_26337 HSPH1 1
+s_12983 COL6A3 1
+s_1376 ADSS 1
+s_45449 PYHIN1 1
+s_49629 SEC22C 1
+s_20204 FAM86A 1
+s_24920 HDAC9 1
+s_14961 DAPK1 1
+s_23900 GPR98 2
+s_14485 CXorf27 1
+s_61808 WDR66 1
+s_55855 TCF7 1
+s_44652 PSG8 1
+s_46608 RCCD1 1
+s_61175 VCAM1 1
+s_27453 INCA1 1
+s_28987 KDM4C 1
+s_20613 FBXO7 1
+s_7715 C2orf70 3
+s_3902 ASB9 1
+s_64098 ZNF534 1
+s_31108 LIN7B 1
+s_3383 ARHGEF1 1
+s_7626 C2orf43 1
+s_52247 SLC8A1 1
+s_54498 STOX1 1
+s_12160 CLDN17 1
+s_16224 DMD 1
+s_41715 PHLDB2 1
+s_12197 CLDN7 1
+s_51239 SLC22A16 1
+s_41286 PEPD 1
+s_2367 ANGPTL4 1
+s_59289 TSC22D4 1
+s_22437 GCFC2 1
+s_24343 GSTO2 1
+s_32783 MAPKAPK5 1
+s_37032 NINJ1 1
+s_49065 SASH3 1
+s_60466 UGT1A1 1
+s_26043 HPSE2 2
+s_21199 FLNA 1
+s_41054 PDGFRA 1
+s_1820 AKNA 1
+s_19548 FAM166A 1
+s_43967 PRDX5 1
+s_51905 SLC39A8 1
+s_22723 GGT5 5
+s_13242 COX6C 1
+s_27668 IP6K1 1
+s_64491 ZNF692 1
+s_61982 WHSC1L1 2
+s_48495 RSAD1 1
+s_34351 MOCS3 1
+s_12069 CLCA1 3
+s_22023 GABRR1 1
+s_12812 COASY 2
+s_40068 PAIP1 1
+s_11513 CGREF1 2
+s_32119 LY6K 1
+s_60743 UQCR11 1
+s_56354 TGFBR1 1
+s_3062 APOL2 1
+s_20525 FBXO25 1
+s_55591 TBC1D7 1
+s_14987 DARS2 1
+s_63195 ZMAT2 1
+s_41936 PIK3C2G 1
+s_56092 TEP1 1
+s_61284 VIT 1
+s_10035 CCND2 1
+s_43744 PPP6R3 2
+s_48110 RPL10L 1
+s_39381 OR5H15 1
+s_6827 C17orf90 2
+s_8795 CADPS 1
+s_55301 TAF9 1
+s_25756 HNRNPM 1
+s_61177 VCAN 1
+s_22932 GLB1 1
+s_55751 TCEA2 1
+s_39419 OR5T3 1
+s_33669 MEX3A 1
+s_42714 PLXNC1 1
+s_23239 GNAT1 1
+s_4546 ATPAF1 1
+s_64432 ZNF671 1
+s_31346 LOXHD1 1
+s_46353 RBFOX2 1
+s_8848 CALHM2 1
+s_27039 IL12RB1 1
+s_62824 ZCCHC9 1
+s_7498 C20orf96 1
+s_43406 PPIE 1
+s_54925 SYN1 1
+s_27284 IL31RA 1
+s_63774 ZNF37A 1
+s_43643 PPP1R8 1
+s_63149 ZIC2 1
+s_26251 HSP90AB1 1
+s_46773 RELL2 1
+s_64868 ZP4 1
+s_626 ACLY 1
+s_40694 PCED1A 1
+s_15888 DHTKD1 1
+s_53641 SPP1 1
+s_21822 FXR1 1
+s_53660 SPR 1
+s_29906 KLKB1 1
+s_1901 ALAS2 1
+s_45130 PTPN2 1
+s_43535 PPP1R13B 2
+s_15855 DHRS12 1
+s_13602 CRH 1
+s_51848 SLC39A1 1
+s_61205 VDR 1
+s_18989 EXOC7 1
+s_22294 GATA1 2
+s_34584 MRAS 1
+s_33140 MCFD2 1
+s_34546 MPST 1
+s_27208 IL21R 1
+s_14576 CYB5R4 1
+s_43745 PPP6R3 1
+s_41675 PHF8 1
+s_41243 PEBP4 2
+s_42685 PLXNA1 1
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+s_7162 C1orf144 0
+s_7234 C1orf198 0
+s_7341 C1orf63 0
+s_747 ACSL1 0
+s_76 AARS2 0
+s_7674 C2orf57 0
+s_7681 C2orf62 0
+s_7692 C2orf63 0
+s_77 AARSD1 0
+s_78 AARSD1 0
+s_781 ACSS1 0
+s_786 ACSS2 0
+s_7940 C4orf26 0
+s_7970 C4orf37 0
+s_8000 C4orf52 0
+s_804 ACTB 0
+s_8073 C5orf51 0
+s_8141 C6orf162 0
+s_8227 C7orf10 0
+s_8281 C7orf59 0
+s_8318 C8A 0
+s_8403 C9orf100 0
+s_8470 C9orf24 0
+s_8699 CACNA1G 0
+s_8705 CACNA1I 0
+s_871 ACTR8 0
+s_874 ACTR8 0
+s_8757 CACNG5 0
+s_8797 CADPS 0
+s_8879 CALR 0
+s_8910 CAMK2B 0
+s_893 ACVR1B 0
+s_8930 CAMKK1 0
+s_8954 CAMSAP1 0
+s_9064 CAPRIN1 0
+s_9077 CAPSL 0
+s_9109 CARD17 0
+s_913 ACY1 0
+s_9171 CASD1 0
+s_9196 CASP10 0
+s_9285 CATSPER3 0
+s_9506 CCDC120 0
+s_9507 CCDC121 0
+s_952 ADAM12 0
+s_9584 CCDC149 0
+s_964 ADAM18 0
+s_9646 CCDC170 0
+s_9710 CCDC40 0
+s_9732 CCDC48 0
+s_976 ADAM21 0
+s_9763 CCDC62 0
+s_9868 CCDC89 0
+s_991 ADAM30 0
+s_9925 CCL1 0
+s_9973 CCL26 0
diff -r 93f268840b0c -r 9cd937788131 test-data/out.count_multi.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/out.count_multi.txt Wed Apr 04 11:03:44 2018 -0400
@@ -0,0 +1,2551 @@
+sgRNA Gene test1_fastq_gz test2_fastq_gz
+s_47512 RNF111 1 0
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+s_34264 MMRN1 1 0
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+s_23990 GPX7 1 0
+s_20268 FANCC 1 0
+s_14157 CTLA4 1 0
+s_36773 NEURL4 18 3
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+s_46620 RCN1 1 0
+s_55436 TAS2R3 1 0
+s_57947 TMPRSS2 1 1
+s_6438 C14orf159 1 0
+s_33846 MGST2 1 0
+s_16328 DNAH6 1 0
+s_17875 EIF4G1 1 0
+s_2305 ANAPC11 1 0
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+s_55329 TAL1 1 0
+s_57926 TMPRSS11E 8 0
+s_38414 NUP98 4 0
+s_50044 SERPINF1 1 0
+s_9257 CASR 1 0
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+s_56478 THBS3 1 0
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+s_4937 BAIAP3 2 0
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+s_19157 FABP12 1 0
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diff -r 93f268840b0c -r 9cd937788131 test-data/out.countsummary.pdf
Binary file test-data/out.countsummary.pdf has changed
diff -r 93f268840b0c -r 9cd937788131 test-data/out.countsummary.txt
--- a/test-data/out.countsummary.txt Sat Feb 17 10:41:41 2018 -0500
+++ b/test-data/out.countsummary.txt Wed Apr 04 11:03:44 2018 -0400
@@ -1,2 +1,2 @@
File Label Reads Mapped Percentage TotalsgRNAs Zerocounts GiniIndex NegSelQC NegSelQCPval NegSelQCPvalPermutation NegSelQCPvalPermutationFDR NegSelQCGene
-input.gz sample1 2500 1453 0.5812 2550 1276 0.5267 0 1 1 1 0.0
+input_0.gz test1_fastq_gz 2500 1453 0.5812 2550 1276 0.5267 0 1 1 1 0.0
diff -r 93f268840b0c -r 9cd937788131 test-data/out.countsummary_multi.pdf
Binary file test-data/out.countsummary_multi.pdf has changed
diff -r 93f268840b0c -r 9cd937788131 test-data/out.mle.log.txt
--- a/test-data/out.mle.log.txt Sat Feb 17 10:41:41 2018 -0500
+++ b/test-data/out.mle.log.txt Wed Apr 04 11:03:44 2018 -0400
@@ -1,749 +1,57 @@
-INFO @ Mon, 12 Feb 2018 21:46:26: Parameters: /home/maria/miniconda3/envs/mulled-v1-b1e6893952d2d7e4d51a13d040adcd7bea052bfdc57a24d59056014db875e749/bin/mageck mle -k /tmp/tmpRFR3vr/files/000/dataset_1.dat -d /tmp/tmpRFR3vr/files/000/dataset_2.dat -n output --norm-method median --genes-varmodeling 1000 --permutation-round 10 --adjust-method fdr --threads 1
-INFO @ Mon, 12 Feb 2018 21:46:27: Cannot parse design matrix as a string; try to parse it as a file name ...
-INFO @ Mon, 12 Feb 2018 21:46:27: Design matrix:
-INFO @ Mon, 12 Feb 2018 21:46:27: [[1. 0. 0.]
-INFO @ Mon, 12 Feb 2018 21:46:27: [1. 0. 0.]
-INFO @ Mon, 12 Feb 2018 21:46:27: [1. 1. 0.]
-INFO @ Mon, 12 Feb 2018 21:46:27: [1. 0. 1.]]
-INFO @ Mon, 12 Feb 2018 21:46:27: Beta labels:baseline,HL60,KBM7
-INFO @ Mon, 12 Feb 2018 21:46:27: Included samples:HL60.initial,KBM7.initial,HL60.final,KBM7.final
-INFO @ Mon, 12 Feb 2018 21:46:27: Loaded samples:HL60.initial;KBM7.initial;HL60.final;KBM7.final
-INFO @ Mon, 12 Feb 2018 21:46:27: Sample index: 0;1;2;3
-INFO @ Mon, 12 Feb 2018 21:46:27: Loaded 100 genes.
-DEBUG @ Mon, 12 Feb 2018 21:46:27: Initial (total) size factor: 1.6654412961322171 2.025116092944715 0.720025234995028 0.6592307725342162
-DEBUG @ Mon, 12 Feb 2018 21:46:27: Median factor: 1.4705915949061357 1.773663484525946 0.6311218804203026 0.5731039100868989
-INFO @ Mon, 12 Feb 2018 21:46:27: Final size factor: 1.4705915949061357 1.773663484525946 0.6311218804203026 0.5731039100868989
-INFO @ Mon, 12 Feb 2018 21:46:27: size factor: 0.6799984465189518,0.5638048078028025,1.5844800046134337,1.744884273862957
-INFO @ Mon, 12 Feb 2018 21:46:27: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:46:27: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:46:27: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:46:27: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:46:27: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:46:27: Modeling the mean and variance ...
-INFO @ Mon, 12 Feb 2018 21:46:27: Linear regression: y=-0.902175602829449x+14.539230037913281
-INFO @ Mon, 12 Feb 2018 21:46:27: Run the algorithm for the second time ...
-WARNING @ Mon, 12 Feb 2018 21:46:27: A1CF: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:46:27: A1CF: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:46:28: A1CF: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:28: A1CF: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:46:29: A1CF: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:29: A1CF: alpha: 0.09
-INFO @ Mon, 12 Feb 2018 21:46:29: Calculating AAAS (1) ...
-WARNING @ Mon, 12 Feb 2018 21:46:29: AAAS: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:46:29: AAAS: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:46:30: AAAS: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:30: AAAS: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:46:31: AAAS: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:31: AAAS: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:46:31: AAK1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:46:31: AAK1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:46:31: AAK1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:31: AAK1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:46:32: AAK1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:32: AAK1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:46:32: AATF: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:46:32: AATF: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:46:33: AATF: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:33: AATF: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:46:33: AATF: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:33: AATF: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:46:33: AATK: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:46:33: AATK: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:46:34: AATK: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:34: AATK: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:46:35: AATK: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:35: AATK: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:46:35: ABCB8: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:46:35: ABCB8: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:46:36: ABCB8: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:36: ABCB8: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:46:37: ABCB8: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:37: ABCB8: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:46:37: ABCC1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:46:37: ABCC1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:46:38: ABCC1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:38: ABCC1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:46:38: ABCC1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:38: ABCC1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:46:38: ABCF1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:46:38: ABCF1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:46:39: ABCF1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:39: ABCF1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:46:40: ABCF1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:40: ABCF1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:46:40: ABHD14B: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:46:40: ABHD14B: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:46:41: ABHD14B: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:41: ABHD14B: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:46:42: ABHD14B: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:42: ABHD14B: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:46:42: ABI1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:46:42: ABI1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:46:43: ABI1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:43: ABI1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:46:44: ABI1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:44: ABI1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:46:44: ABL1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:46:44: ABL1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:46:44: ABL1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:44: ABL1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:46:45: ABL1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:45: ABL1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:46:45: ABL2: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:46:45: ABL2: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:46:46: ABL2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:46: ABL2: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:46:47: ABL2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:47: ABL2: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:46:47: ABLIM2: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:46:47: ABLIM2: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:46:48: ABLIM2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:48: ABLIM2: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:46:49: ABLIM2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:49: ABLIM2: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:46:49: ABT1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:46:49: ABT1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:46:50: ABT1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:50: ABT1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:46:50: ABTB1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:46:50: ABTB1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:46:51: ABTB1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:51: ABTB1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:46:52: ABTB1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:52: ABTB1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:46:52: ACAD11: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:46:52: ACAD11: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:46:53: ACAD11: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:53: ACAD11: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:46:54: ACAD11: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:54: ACAD11: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:46:54: ACAD9: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:46:54: ACAD9: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:46:55: ACAD9: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:55: ACAD9: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:46:55: ACAD9: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:55: ACAD9: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:46:56: ACAT2: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:46:56: ACAT2: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:46:56: ACAT2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:56: ACAT2: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:46:57: ACAT2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:57: ACAT2: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:46:57: ACBD6: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:46:57: ACBD6: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:46:58: ACBD6: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:58: ACBD6: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:46:59: ACBD6: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:46:59: ACBD6: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:46:59: ACD: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:46:59: ACD: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:00: ACD: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:00: ACD: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:00: ACD: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:00: ACD: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:00: ACHE: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:00: ACHE: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:01: ACHE: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:01: ACHE: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:02: ACHE: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:02: ACHE: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:02: ACIN1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:02: ACIN1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:03: ACIN1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:03: ACIN1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:04: ACIN1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:04: ACIN1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:04: ACLY: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:04: ACLY: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:05: ACLY: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:05: ACLY: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:05: ACO2: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:05: ACO2: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:06: ACO2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:06: ACO2: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:07: ACO2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:07: ACO2: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:07: ACP1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:07: ACP1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:08: ACP1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:08: ACP1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:08: ACP1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:08: ACP1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:08: ACRC: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:08: ACRC: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:09: ACRC: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:09: ACRC: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:10: ACRC: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:10: ACRC: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:10: ACSL6: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:10: ACSL6: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:11: ACSL6: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:11: ACSL6: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:11: ACSL6: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:11: ACSL6: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:11: ACSS2: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:11: ACSS2: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:12: ACSS2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:12: ACSS2: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:13: ACSS2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:13: ACSS2: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:13: ACTL6A: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:13: ACTL6A: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:13: ACTL6A: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:13: ACTL6A: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:14: ACTL6A: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:14: ACTL6A: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:14: ACTL6B: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:14: ACTL6B: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:15: ACTL6B: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:15: ACTL6B: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:16: ACTL6B: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:16: ACTL6B: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:16: ACTL7A: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:16: ACTL7A: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:16: ACTL7A: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:16: ACTL7A: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:17: ACTL7A: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:17: ACTL7A: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:17: ACTN1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:17: ACTN1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:18: ACTN1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:18: ACTN1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:19: ACTN1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:19: ACTN1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:19: ACTN4: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:19: ACTN4: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:19: ACTN4: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:19: ACTN4: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:20: ACTN4: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:20: ACTN4: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:20: ACTR1A: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:20: ACTR1A: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:21: ACTR1A: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:21: ACTR1A: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:22: ACTR1A: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:22: ACTR1A: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:22: ACTR3: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:22: ACTR3: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:22: ACTR3: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:22: ACTR3: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:23: ACTR3: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:23: ACTR3: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:23: ACTR5: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:23: ACTR5: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:24: ACTR5: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:24: ACTR5: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:25: ACTR5: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:25: ACTR5: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:25: ACTR8: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:25: ACTR8: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:25: ACTR8: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:25: ACTR8: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:26: ACTR8: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:26: ACTR8: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:26: ACTRT3: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:26: ACTRT3: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:27: ACTRT3: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:27: ACTRT3: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:28: ACTRT3: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:28: ACTRT3: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:28: ACVR1B: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:28: ACVR1B: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:28: ACVR1B: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:28: ACVR1B: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:29: ACVR1B: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:29: ACVR1B: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:29: ACVR1C: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:29: ACVR1C: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:30: ACVR1C: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:30: ACVR1C: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:30: ACVR1C: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:30: ACVR1C: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:30: ACVR1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:30: ACVR1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:31: ACVR1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:31: ACVR1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:32: ACVR1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:32: ACVR1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:32: ACVR2A: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:32: ACVR2A: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:33: ACVR2A: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:33: ACVR2A: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:33: ACVR2A: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:33: ACVR2A: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:33: ACVR2B: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:33: ACVR2B: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:34: ACVR2B: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:34: ACVR2B: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:35: ACVR2B: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:35: ACVR2B: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:35: ACVRL1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:35: ACVRL1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:36: ACVRL1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:36: ACVRL1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:36: ACVRL1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:36: ACVRL1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:36: ADAD1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:36: ADAD1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:37: ADAD1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:37: ADAD1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:38: ADAD1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:38: ADAD1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:38: ADAM10: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:38: ADAM10: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:38: ADAM10: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:38: ADAM10: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:39: ADAM10: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:39: ADAM10: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:39: ADAM12: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:39: ADAM12: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:40: ADAM12: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:40: ADAM12: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:41: ADAM12: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:41: ADAM12: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:41: ADAMTS5: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:41: ADAMTS5: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:41: ADAMTS5: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:41: ADAMTS5: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:42: ADAMTS5: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:42: ADAMTS5: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:42: ADAP1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:42: ADAP1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:43: ADAP1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:43: ADAP1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:44: ADAP1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:44: ADAP1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:44: ADARB1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:44: ADARB1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:44: ADARB1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:44: ADARB1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:45: ADARB1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:45: ADARB1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:45: ADARB2: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:45: ADARB2: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:46: ADARB2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:46: ADARB2: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:47: ADARB2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:47: ADARB2: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:47: ADAR: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:47: ADAR: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:48: ADAR: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:48: ADAR: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:48: ADAR: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:48: ADAR: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:48: ADCK1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:48: ADCK1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:49: ADCK1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:49: ADCK1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:50: ADCK1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:50: ADCK1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:50: ADCK2: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:50: ADCK2: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:51: ADCK2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:51: ADCK2: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:51: ADCK2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:51: ADCK2: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:51: ADCK3: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:51: ADCK3: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:52: ADCK3: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:52: ADCK3: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:53: ADCK3: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:53: ADCK3: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:53: ADCK4: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:53: ADCK4: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:54: ADCK4: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:54: ADCK4: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:54: ADCK4: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:54: ADCK4: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:54: ADCK5: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:54: ADCK5: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:55: ADCK5: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:55: ADCK5: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:56: ADCK5: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:56: ADCK5: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:56: ADCY1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:56: ADCY1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:57: ADCY1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:57: ADCY1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:57: ADCY1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:57: ADCY1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:57: ADD1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:57: ADD1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:47:58: ADD1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:58: ADD1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:47:59: ADD1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:47:59: ADD1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:47:59: ADD3: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:47:59: ADD3: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:00: ADD3: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:00: ADD3: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:00: ADD3: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:00: ADD3: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:00: ADH5: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:00: ADH5: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:01: ADH5: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:01: ADH5: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:02: ADH5: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:02: ADH5: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:02: ADH7: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:02: ADH7: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:03: ADH7: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:03: ADH7: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:04: ADH7: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:04: ADH7: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:04: ADI1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:04: ADI1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:04: ADI1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:04: ADI1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:05: ADI1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:05: ADI1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:06: ADIRF: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:06: ADIRF: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:06: ADIRF: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:06: ADIRF: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:07: ADIRF: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:07: ADIRF: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:07: ADK: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:07: ADK: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:08: ADK: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:08: ADK: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:08: ADK: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:08: ADK: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:09: ADNP2: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:09: ADNP2: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:09: ADNP2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:09: ADNP2: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:10: ADNP2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:10: ADNP2: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:10: ADNP: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:10: ADNP: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:11: ADNP: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:11: ADNP: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:12: ADNP: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:12: ADNP: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:12: ADPRHL2: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:12: ADPRHL2: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:12: ADPRHL2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:12: ADPRHL2: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:13: ADPRHL2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:13: ADPRHL2: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:13: ADRA1A: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:13: ADRA1A: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:14: ADRA1A: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:14: ADRA1A: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:14: ADRA1A: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:14: ADRA1A: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:14: ADRA1B: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:14: ADRA1B: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:15: ADRA1B: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:15: ADRA1B: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:16: ADRA1B: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:16: ADRA1B: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:16: ADRB1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:16: ADRB1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:17: ADRB1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:17: ADRB1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:18: ADRB1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:18: ADRB1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:18: ADRB2: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:18: ADRB2: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:19: ADRB2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:19: ADRB2: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:20: ADRB2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:20: ADRB2: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:20: ADRB3: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:20: ADRB3: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:21: ADRB3: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:21: ADRB3: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:21: ADRB3: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:21: ADRB3: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:21: ADRBK1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:21: ADRBK1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:22: ADRBK1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:22: ADRBK1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:23: ADRBK1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:23: ADRBK1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:23: ADRBK2: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:23: ADRBK2: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:24: ADRBK2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:24: ADRBK2: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:25: ADRBK2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:25: ADRBK2: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:25: ADRM1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:25: ADRM1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:26: ADRM1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:26: ADRM1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:26: ADRM1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:26: ADRM1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:27: AEBP1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:27: AEBP1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:27: AEBP1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:27: AEBP1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:28: AEBP1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:28: AEBP1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:28: AEBP2: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:28: AEBP2: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:29: AEBP2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:29: AEBP2: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:30: AEBP2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:30: AEBP2: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:30: AEN: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:30: AEN: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:31: AEN: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:31: AEN: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:31: AEN: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:31: AEN: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:31: AES: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:31: AES: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:32: AES: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:32: AES: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:33: AES: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:33: AES: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:33: AFAP1L2: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:33: AFAP1L2: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:34: AFAP1L2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:34: AFAP1L2: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:34: AFAP1L2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:34: AFAP1L2: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:34: AFF1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:34: AFF1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:35: AFF1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:35: AFF1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:36: AFF1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:36: AFF1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:36: AFF2: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:36: AFF2: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:37: AFF2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:37: AFF2: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:37: AFF2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:37: AFF2: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:37: AFF3: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:37: AFF3: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:38: AFF3: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:38: AFF3: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:39: AFF3: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:39: AFF3: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:39: AFF4: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:39: AFF4: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:40: AFF4: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:40: AFF4: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:40: AFF4: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:40: AFF4: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:40: AFMID: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:40: AFMID: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:41: AFMID: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:41: AFMID: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:42: AFMID: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:42: AFMID: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:42: AFTPH: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:42: AFTPH: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:43: AFTPH: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:43: AFTPH: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:43: AFTPH: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:43: AFTPH: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:43: AGAP2: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:43: AGAP2: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:44: AGAP2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:44: AGAP2: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:45: AGAP2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:45: AGAP2: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:45: AGAP3: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:45: AGAP3: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:45: AGAP3: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:45: AGAP3: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:46: AGAP3: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:46: AGAP3: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:46: AGBL5: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:46: AGBL5: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:47: AGBL5: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:47: AGBL5: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:48: AGBL5: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:48: AGBL5: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:48: AGFG1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:48: AGFG1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:48: AGFG1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:48: AGFG1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:49: AGFG1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:49: AGFG1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:50: AGL: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:50: AGL: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:51: AGL: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:51: AGL: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:51: AGPAT3: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:51: AGPAT3: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:52: AGPAT3: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:52: AGPAT3: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:52: AGPAT3: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:52: AGPAT3: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:52: AGPAT5: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:52: AGPAT5: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:53: AGPAT5: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:53: AGPAT5: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:54: AGPAT5: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:54: AGPAT5: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:54: AGTPBP1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:54: AGTPBP1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:55: AGTPBP1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:55: AGTPBP1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:55: AGTPBP1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:55: AGTPBP1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:55: AHCTF1: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:55: AHCTF1: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:56: AHCTF1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:56: AHCTF1: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:57: AHCTF1: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:57: AHCTF1: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:57: AHCY: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:57: AHCY: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:58: AHCY: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:58: AHCY: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:48:58: AHCY: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:58: AHCY: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:48:58: AHNAK2: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:48:58: AHNAK2: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:48:59: AHNAK2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:48:59: AHNAK2: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:49:00: AHNAK2: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:49:00: AHNAK2: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:49:01: AHNAK: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:49:01: AHNAK: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:49:01: AHNAK: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:49:01: AHNAK: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:49:02: AHNAK: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:49:02: AHNAK: alpha: 0.09
-WARNING @ Mon, 12 Feb 2018 21:49:02: AHRR: beta value does not converge. Try to increase the value of alpha ..
-WARNING @ Mon, 12 Feb 2018 21:49:02: AHRR: alpha: 0.01
-WARNING @ Mon, 12 Feb 2018 21:49:03: AHRR: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:49:03: AHRR: alpha: 0.03
-WARNING @ Mon, 12 Feb 2018 21:49:04: AHRR: reaches the maximum number of iterations.
-WARNING @ Mon, 12 Feb 2018 21:49:04: AHRR: alpha: 0.09
-INFO @ Mon, 12 Feb 2018 21:49:04: Permuting groups of gene with 9 sgRNAs per gene. Group progress: 1/2
-INFO @ Mon, 12 Feb 2018 21:49:04: Start permuting 10 rounds ...
-INFO @ Mon, 12 Feb 2018 21:49:04: Collecting 999 sgRNAs from 100 genes.
-INFO @ Mon, 12 Feb 2018 21:49:04: Permuting round 0 ...
-INFO @ Mon, 12 Feb 2018 21:49:04: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:49:04: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:49:04: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:49:04: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:49:04: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:49:04: Permuting round 1 ...
-INFO @ Mon, 12 Feb 2018 21:49:05: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:49:05: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:49:05: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:49:05: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:49:05: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:49:05: Permuting round 2 ...
-INFO @ Mon, 12 Feb 2018 21:49:05: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:49:05: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:49:05: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:49:06: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:49:06: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:49:06: Permuting round 3 ...
-INFO @ Mon, 12 Feb 2018 21:49:06: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:49:06: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:49:06: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:49:07: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:49:07: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:49:07: Permuting round 4 ...
-INFO @ Mon, 12 Feb 2018 21:49:07: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:49:07: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:49:07: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:49:08: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:49:08: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:49:08: Permuting round 5 ...
-INFO @ Mon, 12 Feb 2018 21:49:08: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:49:08: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:49:08: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:49:09: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:49:09: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:49:09: Permuting round 6 ...
-INFO @ Mon, 12 Feb 2018 21:49:09: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:49:09: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:49:09: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:49:09: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:49:09: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:49:10: Permuting round 7 ...
-INFO @ Mon, 12 Feb 2018 21:49:10: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:49:10: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:49:10: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:49:10: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:49:10: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:49:10: Permuting round 8 ...
-INFO @ Mon, 12 Feb 2018 21:49:10: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:49:10: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:49:10: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:49:11: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:49:11: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:49:11: Permuting round 9 ...
-INFO @ Mon, 12 Feb 2018 21:49:11: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:49:11: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:49:11: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:49:12: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:49:12: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:49:12: Assigning p values...
-INFO @ Mon, 12 Feb 2018 21:49:12: Permuting groups of gene with 10 sgRNAs per gene. Group progress: 2/2
-INFO @ Mon, 12 Feb 2018 21:49:12: Start permuting 10 rounds ...
-INFO @ Mon, 12 Feb 2018 21:49:12: Collecting 999 sgRNAs from 100 genes.
-INFO @ Mon, 12 Feb 2018 21:49:12: Permuting round 0 ...
-INFO @ Mon, 12 Feb 2018 21:49:12: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:49:12: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:49:12: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:49:13: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:49:13: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:49:13: Permuting round 1 ...
-INFO @ Mon, 12 Feb 2018 21:49:13: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:49:13: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:49:13: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:49:14: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:49:14: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:49:14: Permuting round 2 ...
-INFO @ Mon, 12 Feb 2018 21:49:14: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:49:14: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:49:14: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:49:15: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:49:15: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:49:15: Permuting round 3 ...
-INFO @ Mon, 12 Feb 2018 21:49:15: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:49:15: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:49:15: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:49:16: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:49:16: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:49:16: Permuting round 4 ...
-INFO @ Mon, 12 Feb 2018 21:49:16: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:49:16: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:49:16: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:49:16: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:49:16: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:49:17: Permuting round 5 ...
-INFO @ Mon, 12 Feb 2018 21:49:17: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:49:17: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:49:17: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:49:17: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:49:17: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:49:18: Permuting round 6 ...
-INFO @ Mon, 12 Feb 2018 21:49:18: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:49:18: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:49:18: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:49:19: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:49:19: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:49:19: Permuting round 7 ...
-INFO @ Mon, 12 Feb 2018 21:49:19: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:49:19: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:49:19: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:49:20: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:49:20: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:49:20: Permuting round 8 ...
-INFO @ Mon, 12 Feb 2018 21:49:20: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:49:20: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:49:20: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:49:21: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:49:21: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:49:21: Permuting round 9 ...
-INFO @ Mon, 12 Feb 2018 21:49:21: Thread 0 started.
-INFO @ Mon, 12 Feb 2018 21:49:21: Thread 0: total 100 instances.
-INFO @ Mon, 12 Feb 2018 21:49:21: Thread 0: Calculating AAAS (1) ...
-INFO @ Mon, 12 Feb 2018 21:49:21: Thread 0 completed.
-INFO @ Mon, 12 Feb 2018 21:49:21: All threads completed.
-INFO @ Mon, 12 Feb 2018 21:49:22: Assigning p values...
-INFO @ Mon, 12 Feb 2018 21:49:22: Writing gene results to output.gene_summary.txt
-INFO @ Mon, 12 Feb 2018 21:49:22: Writing sgRNA results to output.sgrna_summary.txt
+INFO @ Sun, 25 Mar 2018 22:27:41: Parameters: /Users/doylemaria/miniconda3/envs/mulled-v1-9ee130591ca78526e74a59d8d6dc03cb7db20645470975762936caeac62972dc/bin/mageck mle -k /private/var/folders/zn/m_qvr9zd7tq0wdtsbq255f8xypj_zg/T/tmpELNsjE/files/000/dataset_28.dat -d /private/var/folders/zn/m_qvr9zd7tq0wdtsbq255f8xypj_zg/T/tmpELNsjE/files/000/dataset_29.dat -n output --norm-method median --threads 1
+INFO @ Sun, 25 Mar 2018 22:27:42: Cannot parse design matrix as a string; try to parse it as a file name ...
+INFO @ Sun, 25 Mar 2018 22:27:42: Design matrix:
+INFO @ Sun, 25 Mar 2018 22:27:42: [[1. 0. 0.]
+INFO @ Sun, 25 Mar 2018 22:27:42: [1. 0. 0.]
+INFO @ Sun, 25 Mar 2018 22:27:42: [1. 1. 0.]
+INFO @ Sun, 25 Mar 2018 22:27:42: [1. 0. 1.]]
+INFO @ Sun, 25 Mar 2018 22:27:42: Beta labels:baseline,HL60,KBM7
+INFO @ Sun, 25 Mar 2018 22:27:42: Included samples:HL60.initial,KBM7.initial,HL60.final,KBM7.final
+INFO @ Sun, 25 Mar 2018 22:27:42: Loaded samples:HL60.initial;KBM7.initial;HL60.final;KBM7.final
+INFO @ Sun, 25 Mar 2018 22:27:42: Sample index: 0;1;2;3
+INFO @ Sun, 25 Mar 2018 22:27:42: Loaded 100 genes.
+DEBUG @ Sun, 25 Mar 2018 22:27:42: Initial (total) size factor: 1.6654412961322171 2.025116092944715 0.720025234995028 0.6592307725342162
+DEBUG @ Sun, 25 Mar 2018 22:27:42: Median factor: 1.4705915949061357 1.773663484525946 0.6311218804203026 0.5731039100868989
+INFO @ Sun, 25 Mar 2018 22:27:42: Final size factor: 1.4705915949061357 1.773663484525946 0.6311218804203026 0.5731039100868989
+INFO @ Sun, 25 Mar 2018 22:27:42: size factor: 0.6799984465189518,0.5638048078028025,1.5844800046134337,1.744884273862957
+INFO @ Sun, 25 Mar 2018 22:27:42: Thread 0 started.
+INFO @ Sun, 25 Mar 2018 22:27:42: Thread 0: total 1 instances.
+INFO @ Sun, 25 Mar 2018 22:27:42: Thread 0 completed.
+INFO @ Sun, 25 Mar 2018 22:27:42: All threads completed.
+INFO @ Sun, 25 Mar 2018 22:27:42: Modeling the mean and variance ...
+INFO @ Sun, 25 Mar 2018 22:27:42: Run the algorithm for the second time ...
+INFO @ Sun, 25 Mar 2018 22:27:42: Calculating AAAS (1) ...
+INFO @ Sun, 25 Mar 2018 22:27:43: Permuting groups of gene with 9 sgRNAs per gene. Group progress: 1/2
+INFO @ Sun, 25 Mar 2018 22:27:43: Start permuting 2 rounds ...
+INFO @ Sun, 25 Mar 2018 22:27:43: Collecting 999 sgRNAs from 100 genes.
+INFO @ Sun, 25 Mar 2018 22:27:43: Permuting round 0 ...
+INFO @ Sun, 25 Mar 2018 22:27:43: Thread 0 started.
+INFO @ Sun, 25 Mar 2018 22:27:43: Thread 0: total 100 instances.
+INFO @ Sun, 25 Mar 2018 22:27:43: Thread 0: Calculating AAAS (1) ...
+INFO @ Sun, 25 Mar 2018 22:27:45: Thread 0 completed.
+INFO @ Sun, 25 Mar 2018 22:27:45: All threads completed.
+INFO @ Sun, 25 Mar 2018 22:27:45: Permuting round 1 ...
+INFO @ Sun, 25 Mar 2018 22:27:45: Thread 0 started.
+INFO @ Sun, 25 Mar 2018 22:27:45: Thread 0: total 100 instances.
+INFO @ Sun, 25 Mar 2018 22:27:45: Thread 0: Calculating AAAS (1) ...
+INFO @ Sun, 25 Mar 2018 22:27:46: Thread 0 completed.
+INFO @ Sun, 25 Mar 2018 22:27:46: All threads completed.
+INFO @ Sun, 25 Mar 2018 22:27:46: Assigning p values...
+INFO @ Sun, 25 Mar 2018 22:27:46: Permuting groups of gene with 10 sgRNAs per gene. Group progress: 2/2
+INFO @ Sun, 25 Mar 2018 22:27:46: Start permuting 2 rounds ...
+INFO @ Sun, 25 Mar 2018 22:27:46: Collecting 999 sgRNAs from 100 genes.
+INFO @ Sun, 25 Mar 2018 22:27:46: Permuting round 0 ...
+INFO @ Sun, 25 Mar 2018 22:27:47: Thread 0 started.
+INFO @ Sun, 25 Mar 2018 22:27:47: Thread 0: total 100 instances.
+INFO @ Sun, 25 Mar 2018 22:27:47: Thread 0: Calculating AAAS (1) ...
+INFO @ Sun, 25 Mar 2018 22:27:48: Thread 0 completed.
+INFO @ Sun, 25 Mar 2018 22:27:48: All threads completed.
+INFO @ Sun, 25 Mar 2018 22:27:49: Permuting round 1 ...
+INFO @ Sun, 25 Mar 2018 22:27:49: Thread 0 started.
+INFO @ Sun, 25 Mar 2018 22:27:49: Thread 0: total 100 instances.
+INFO @ Sun, 25 Mar 2018 22:27:49: Thread 0: Calculating AAAS (1) ...
+INFO @ Sun, 25 Mar 2018 22:27:50: Thread 0 completed.
+INFO @ Sun, 25 Mar 2018 22:27:50: All threads completed.
+INFO @ Sun, 25 Mar 2018 22:27:50: Assigning p values...
+INFO @ Sun, 25 Mar 2018 22:27:50: Writing gene results to output.gene_summary.txt
+INFO @ Sun, 25 Mar 2018 22:27:50: Writing sgRNA results to output.sgrna_summary.txt
diff -r 93f268840b0c -r 9cd937788131 test-data/out.normcounts.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/out.normcounts.txt Wed Apr 04 11:03:44 2018 -0400
@@ -0,0 +1,2551 @@
+sgRNA Gene test1_fastq_gz
+s_47512 RNF111 2.0
+s_24835 HCFC1R1 2.0
+s_14784 CYP4B1 8.0
+s_51146 SLC18A1 2.0
+s_58960 TRIM5 2.0
+s_48256 RPRD2 2.0
+s_30297 KRTAP5-5 2.0
+s_14555 CYB5B 2.0
+s_39959 PAAF1 2.0
+s_45293 PUF60 2.0
+s_49358 SCN8A 2.0
+s_64995 ZYG11A 2.0
+s_4029 ASTE1 2.0
+s_45554 R3HDML 2.0
+s_34264 MMRN1 2.0
+s_37459 NOL6 2.0
+s_23990 GPX7 2.0
+s_20268 FANCC 2.0
+s_14157 CTLA4 2.0
+s_36773 NEURL4 36.0
+s_18804 ETFB 2.0
+s_782 ACSS1 2.0
+s_18272 ENPP2 2.0
+s_46620 RCN1 2.0
+s_55436 TAS2R3 2.0
+s_57947 TMPRSS2 2.0
+s_6438 C14orf159 2.0
+s_33846 MGST2 2.0
+s_16328 DNAH6 2.0
+s_17875 EIF4G1 2.0
+s_2305 ANAPC11 2.0
+s_2500 ANKRD2 2.0
+s_82 AARSD1 2.0
+s_55329 TAL1 2.0
+s_57926 TMPRSS11E 16.0
+s_38414 NUP98 8.0
+s_50044 SERPINF1 2.0
+s_9257 CASR 2.0
+s_63396 ZNF182 2.0
+s_56478 THBS3 2.0
+s_17191 DYRK1A 2.0
+s_11988 CIR1 2.0
+s_43313 PPARD 2.0
+s_44681 PSMA4 2.0
+s_10387 CD320 2.0
+s_64869 ZPBP 2.0
+s_54385 STK17B 2.0
+s_25423 HIST1H4D 2.0
+s_54172 ST8SIA4 18.0
+s_1161 ADCY10 2.0
+s_29184 KIAA0913 2.0
+s_42977 POLD3 2.0
+s_49449 SCUBE1 2.0
+s_24181 GRM4 2.0
+s_52507 SMARCA5 2.0
+s_28674 KCNJ10 2.0
+s_61074 VAMP2 8.0
+s_3954 ASIC2 2.0
+s_2385 ANK1 2.0
+s_18397 EPDR1 2.0
+s_18377 EPB41L4B 2.0
+s_34580 MRAP2 2.0
+s_48676 RUFY3 20.0
+s_691 ACP1 2.0
+s_30460 LAMP2 2.0
+s_42637 PLRG1 2.0
+s_12695 CNOT6 2.0
+s_33316 MECOM 4.0
+s_35081 MSRB2 2.0
+s_58512 TPD52L2 2.0
+s_19912 FAM22F 2.0
+s_45517 QSOX2 2.0
+s_56705 TINAG 2.0
+s_10946 CDKL5 2.0
+s_57473 TMEM211 4.0
+s_57657 TMEM44 2.0
+s_43200 POT1 2.0
+s_19436 FAM135A 2.0
+s_184 ABCB9 2.0
+s_30171 KRT84 2.0
+s_44758 PSMC3IP 2.0
+s_48313 RPS3 2.0
+s_58142 TNFSF12 12.0
+s_59718 TTLL6 14.0
+s_9725 CCDC43 2.0
+s_5135 BCKDHA 2.0
+s_36539 NDUFC2 2.0
+s_27251 IL27RA 2.0
+s_48939 SAMD10 2.0
+s_27343 IL5RA 2.0
+s_28386 KANK2 2.0
+s_27610 INSRR 2.0
+s_2769 AOC3 4.0
+s_58632 TRA2B 24.0
+s_6674 C16orf86 2.0
+s_22902 GJD4 2.0
+s_48278 RPS15A 2.0
+s_61998 WIPF2 2.0
+s_4937 BAIAP3 4.0
+s_54471 STOML1 4.0
+s_19157 FABP12 2.0
+s_5434 BIN1 4.0
+s_42042 PIP5K1A 2.0
+s_7794 C3orf18 2.0
+s_54846 SVIL 2.0
+s_62273 XPA 2.0
+s_45859 RACGAP1 2.0
+s_53626 SPOCK3 2.0
+s_43295 PPAP2C 14.0
+s_11788 CHRDL1 4.0
+s_50636 SHQ1 2.0
+s_16705 DPF1 2.0
+s_39741 OTOF 2.0
+s_27505 INHBE 2.0
+s_707 ACPL2 2.0
+s_15418 DDX3Y 12.0
+s_56018 TEAD4 2.0
+s_44367 PRR12 2.0
+s_25875 HOXB5 2.0
+s_49360 SCN9A 2.0
+s_16244 DMPK 2.0
+s_3909 ASCC2 2.0
+s_55088 SYT6 2.0
+s_54311 STAU1 2.0
+s_53890 SRP72 2.0
+s_11035 CDX1 2.0
+s_18178 EMR3 4.0
+s_16084 DLD 2.0
+s_47207 RHOBTB1 2.0
+s_40267 PARK2 12.0
+s_43104 POLR3B 2.0
+s_2200 AMDHD2 2.0
+s_12738 CNRIP1 2.0
+s_17842 EIF4A3 2.0
+s_57950 TMPRSS3 2.0
+s_62146 WRN 2.0
+s_11055 CEACAM1 2.0
+s_54580 STX2 2.0
+s_29277 KIAA1407 2.0
+s_33428 MEF2A 2.0
+s_59797 TUBB 2.0
+s_18113 EME1 2.0
+s_29839 KLHL8 2.0
+s_18058 ELP2 2.0
+s_49497 SDCBP2 6.0
+s_16874 DRP2 2.0
+s_13572 CREBL2 2.0
+s_20540 FBXO30 2.0
+s_64380 ZNF646 2.0
+s_50366 SH2B1 2.0
+s_2548 ANKRD33B 2.0
+s_41183 PDXP 2.0
+s_16315 DNAH12 2.0
+s_19996 FAM49B 2.0
+s_30751 LDLRAD3 2.0
+s_36960 NGEF 2.0
+s_39015 OR2A2 2.0
+s_26302 HSPB2 2.0
+s_64297 ZNF611 10.0
+s_730 ACSBG1 2.0
+s_50271 SFXN4 2.0
+s_8592 CA6 4.0
+s_13683 CRMP1 2.0
+s_51103 SLC16A7 2.0
+s_63785 ZNF384 2.0
+s_16339 DNAH9 2.0
+s_55936 TCTEX1D1 2.0
+s_14497 CXorf40A 2.0
+s_1123 ADAT1 2.0
+s_41304 PERP 2.0
+s_18719 ESAM 2.0
+s_35118 MSX2 2.0
+s_30128 KRT6A 2.0
+s_402 ABTB1 2.0
+s_32578 MAP1LC3A 2.0
+s_45063 PTMA 2.0
+s_43551 PPP1R14D 2.0
+s_2538 ANKRD32 2.0
+s_40384 PAX1 2.0
+s_29076 KIAA0101 2.0
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+s_52784 SNIP1 0
+s_52787 SNIP1 0
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+s_52989 SNX8 0
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+s_53048 SON 0
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+s_53109 SOSTDC1 0
+s_53151 SOX30 0
+s_53153 SOX30 0
+s_53181 SP100 0
+s_53438 SPDYC 0
+s_53476 SPERT 0
+s_53512 SPI1 0
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+s_53555 SPINK6 0
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+s_54314 STAU2 0
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+s_54480 STON1 0
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+s_56805 TLL1 0
+s_56819 TLR10 0
+s_56826 TLR3 0
+s_56873 TM4SF18 0
+s_57016 TMED10 0
+s_57082 TMEM106C 0
+s_57087 TMEM107 0
+s_57150 TMEM127 0
+s_57173 TMEM132B 0
+s_57181 TMEM132E 0
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+s_57288 TMEM164 0
+s_57299 TMEM167B 0
+s_57409 TMEM194A 0
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+s_57429 TMEM2 0
+s_57475 TMEM212 0
+s_57531 TMEM231 0
+s_57568 TMEM245 0
+s_57700 TMEM54 0
+s_57873 TMF1 0
+s_57992 TMUB1 0
+s_58180 TNIP1 0
+s_58211 TNKS2 0
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+s_58309 TOM1 0
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+s_58503 TPD52 0
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+s_58655 TRAF3 0
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+s_58962 TRIM50 0
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+s_59107 TRMT1L 0
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+s_59539 TTC21A 0
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+s_5974 BTN3A1 0
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+s_60169 UBE2H 0
+s_60209 UBE2Q2 0
+s_60237 UBE2V2 0
+s_60248 UBE3A 0
+s_60250 UBE3B 0
+s_60373 UBXN6 0
+s_60396 UCKL1 0
+s_60423 UEVLD 0
+s_60438 UFSP1 0
+s_60449 UGDH 0
+s_60517 UGT2A1 0
+s_60542 UGT3A1 0
+s_60603 UMODL1 0
+s_60614 UNC119 0
+s_60649 UNC5B 0
+s_6068 C10orf125 0
+s_6071 C10orf128 0
+s_60753 UQCRC2 0
+s_60780 URM1 0
+s_60839 USP15 0
+s_60851 USP19 0
+s_60925 USP4 0
+s_6100 C10orf53 0
+s_6106 C10orf54 0
+s_61149 VAV2 0
+s_61173 VCAM1 0
+s_61178 VCAN 0
+s_61221 VEPH1 0
+s_61263 VIL1 0
+s_61341 VPS13C 0
+s_61344 VPS13D 0
+s_61367 VPS29 0
+s_61529 VWA5A 0
+s_61531 VWA5A 0
+s_61587 WBP1 0
+s_61595 WBP2 0
+s_61623 WDFY1 0
+s_61640 WDHD1 0
+s_61662 WDR16 0
+s_61695 WDR26 0
+s_61739 WDR44 0
+s_6200 C11orf49 0
+s_62019 WISP1 0
+s_62098 WNT5B 0
+s_62114 WNT8A 0
+s_62171 WTAP 0
+s_62249 XKR3 0
+s_62257 XKR6 0
+s_62275 XPC 0
+s_62320 XRCC4 0
+s_62361 YAE1D1 0
+s_62550 ZBBX 0
+s_62559 ZBED6 0
+s_62567 ZBTB1 0
+s_62624 ZBTB37 0
+s_62657 ZBTB47 0
+s_62759 ZC3H7A 0
+s_62845 ZDHHC11 0
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+s_6292 C12orf23 0
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+s_63034 ZFP64 0
+s_63104 ZFYVE27 0
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+s_63114 ZFYVE28 0
+s_63217 ZMIZ2 0
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+s_6326 C12orf49 0
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+s_636 ACO1 0
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+s_63964 ZNF469 0
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+s_64137 ZNF554 0
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+s_6427 C14orf133 0
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+s_64393 ZNF655 0
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+s_64424 ZNF669 0
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+s_64581 ZNF746 0
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+s_64638 ZNF776 0
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+s_64871 ZPBP 0
+s_64878 ZPLD1 0
+s_64898 ZSCAN10 0
+s_64930 ZSCAN30 0
+s_64997 ZYG11A 0
+s_6525 C15orf39 0
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+s_781 ACSS1 0
+s_786 ACSS2 0
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+s_8073 C5orf51 0
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+s_8227 C7orf10 0
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+s_8318 C8A 0
+s_8403 C9orf100 0
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+s_8699 CACNA1G 0
+s_8705 CACNA1I 0
+s_871 ACTR8 0
+s_874 ACTR8 0
+s_8757 CACNG5 0
+s_8797 CADPS 0
+s_8879 CALR 0
+s_8910 CAMK2B 0
+s_893 ACVR1B 0
+s_8930 CAMKK1 0
+s_8954 CAMSAP1 0
+s_9064 CAPRIN1 0
+s_9077 CAPSL 0
+s_9109 CARD17 0
+s_913 ACY1 0
+s_9171 CASD1 0
+s_9196 CASP10 0
+s_9285 CATSPER3 0
+s_9506 CCDC120 0
+s_9507 CCDC121 0
+s_952 ADAM12 0
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+s_964 ADAM18 0
+s_9646 CCDC170 0
+s_9710 CCDC40 0
+s_9732 CCDC48 0
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diff -r 93f268840b0c -r 9cd937788131 test-data/out.test.R
--- a/test-data/out.test.R Sat Feb 17 10:41:41 2018 -0500
+++ b/test-data/out.test.R Wed Apr 04 11:03:44 2018 -0400
@@ -10,7 +10,7 @@
# outputfile='__OUTPUT_FILE__'
targetgenelist=c("ACIN1","ACTR8","AHCY","ACLY","AATF","AGBL5","AHCTF1","ABT1","ADIRF","ABCF1")
# samplelabel=sub('.\\w+.\\w+$','',colnames(gstable)[startindex]);
-samplelabel='HL60.final,KBM7.final_vs_HL60.initial,KBM7.initial neg.'
+samplelabel='HL60_final,KBM7_final_vs_HL60_initial,KBM7_initial neg.'
# You need to write some codes in front of this code:
@@ -116,7 +116,7 @@
# Do not modify the variables beginning with "__"
targetmat=list(c(561.4907165816957,824.0396348113272,428.37415340969943,579.047491896501),c(3424.79939695118,3818.2871009576584,1992.3498917052,690.0506672205338),c(846.6456878299913,985.6508562937211,335.0024675413113,415.97581680707134),c(2432.636481525409,2122.257249136931,1067.465489792653,155.6333179800872),c(1308.1851773762019,2186.1913587343615,1482.5909580453515,997.3120339679854),c(405.68439208520414,268.16807081144486,170.34023773287015,109.85881269182627),c(640.8637498157573,559.4234589775174,711.6436598617687,632.2603542941043),c(946.5969148654764,470.6260845366416,663.0651476194316,457.74505288260946),c(246.9383256170808,177.59474888175154,28.39003962214503,0.0),c(568.8400715107754,612.7018836420428,564.0154538266146,270.64176251684285))
targetgene="ACIN1"
-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
# set up color using RColorBrewer
#library(RColorBrewer)
@@ -151,7 +151,7 @@
# Do not modify the variables beginning with "__"
targetmat=list(c(2484.0819660289676,2349.578527705573,2172.7843657481662,910.9126552363929),c(992.1629154257711,1005.1862786707138,743.8190381001997,200.26346063614164),c(1267.0287897733551,1156.1418152202027,251.09412821363824,42.34141739164138),c(1500.738276518092,1315.977089213779,800.5991173444897,1476.2277955464156),c(1925.5309914189038,2054.7712445618654,194.94493873872918,235.16652091844063),c(351.29916561001374,781.4168950797068,227.75120674654121,624.2498158686586),c(1719.74905340467,1006.9622261595313,356.45271970026533,222.0063506480656),c(903.9706562768137,1445.6212558974576,1482.5909580453515,1055.1023468944147),c(651.152846716469,1081.552020689867,576.0023594448536,1072.2677863775127),c(285.1549712482957,408.46792242802854,99.0496937928171,44.630142656054424))
targetgene="ACTR8"
-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
# set up color using RColorBrewer
#library(RColorBrewer)
@@ -186,7 +186,7 @@
# Do not modify the variables beginning with "__"
targetmat=list(c(301.3235520922712,657.1005708624807,228.38209651592223,137.32351586478285),c(1142.0897559789987,1099.311495578042,112.92926871919911,100.70391163417409),c(789.3207193831689,671.3081507730209,723.6305654800077,588.7745742702564),c(392.45555321286054,412.0198174056636,334.37157777193033,213.99581222261992),c(2009.3136376104133,2235.917888421252,2437.1271791188055,1937.9781176417478),c(1071.5359486598327,406.69197493921104,645.4002340767636,349.602784139093),c(61.7345814042702,218.44154112455442,614.4866353770946,452.5954210376801),c(651.152846716469,879.0940069646701,237.21455328725622,18.88198343140764),c(1625.6773103124485,1410.1023061211074,2146.286995434164,1986.613529510525),c(1053.8974968300413,882.6459019423052,106.6203710253891,105.85354347910344))
targetgene="AHCY"
-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
# set up color using RColorBrewer
#library(RColorBrewer)
@@ -221,7 +221,7 @@
# Do not modify the variables beginning with "__"
targetmat=list(c(1268.498660759171,1411.8782536099247,1136.2324746551822,603.6512884889412),c(327.78122983695846,454.642557137284,51.73296108924205,24.031615276336996),c(132.28838872343613,241.5288584791821,123.02350502929512,65.80085135187511),c(495.34652221997754,586.0626713097802,279.4841678357833,243.74924065998954),c(1009.8013672555626,1102.8633905556771,1237.174837756142,1004.7503910773278),c(877.5129785321263,715.7068379934587,538.1489732819936,594.496387431289),c(1594.8100196103135,1108.1912330221296,605.6541786057605,127.59643349102738),c(314.5523909646148,252.1845434120872,88.95545748272109,359.9020478289517),c(512.984974049769,269.94401830026237,205.67006481820619,126.45207085882086),c(761.3931706526657,475.9539270030942,559.5992254409475,596.7851126957021))
targetgene="ACLY"
-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
# set up color using RColorBrewer
#library(RColorBrewer)
@@ -256,7 +256,7 @@
# Do not modify the variables beginning with "__"
targetmat=list(c(659.9720726313648,809.832054900787,880.7221180558769,802.1982051767731),c(724.6463960072668,1086.8798631563195,695.2405258578626,307.26136674745163),c(836.3565909292796,1289.3378768815162,468.75109865008346,177.94838930811443),c(367.46774645398926,571.85509139924,300.30353022535627,116.72498848506541),c(518.8644579930328,632.2373060190355,627.7353205340956,308.9779106957614),c(405.68439208520414,259.28833336735727,324.27734146183434,166.5047629860492),c(2096.0360257735547,1960.6460276545372,1573.4390848362154,629.9716290296913),c(277.8056163192159,435.1071347602913,182.32714335110919,0.0),c(995.1026573974029,477.7298744919117,728.0467938656747,275.21921304566894),c(2185.6981559083283,1482.9161531626255,1741.8866532609427,1862.4501839161173))
targetgene="AATF"
-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
# set up color using RColorBrewer
#library(RColorBrewer)
@@ -291,7 +291,7 @@
# Do not modify the variables beginning with "__"
targetmat=list(c(640.8637498157573,602.0461987091378,307.2433176885473,192.82510352679924),c(354.23890758164566,280.5997032331675,204.4082852794442,275.79139436177223),c(779.0316224824572,932.3724316291956,778.5179754161547,905.1908420753603),c(624.6951689717818,554.0956165110648,370.96318439602834,558.4489645167836),c(1133.270530064103,1394.1187787217498,639.0913363829536,1131.2024619361487),c(423.32284391499564,412.0198174056636,224.59675789963623,426.84726181303336),c(296.91393913482335,829.3674772777797,489.5704610396565,1233.0507362025292),c(684.959879390236,546.9918265557948,394.30610586312537,566.4595029422292),c(440.96129574478715,630.461358530218,434.6830511035094,457.1728715665062),c(1108.2827233052317,1969.5257650986248,1066.2037102538911,1333.7546478367033))
targetgene="AGBL5"
-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
# set up color using RColorBrewer
#library(RColorBrewer)
@@ -326,7 +326,7 @@
# Do not modify the variables beginning with "__"
targetmat=list(c(196.96271209933826,301.9110730989776,423.9579250240324,34.33087896619571),c(1106.8128523194157,1056.6887558464218,1743.1484327997048,807.3478370217025),c(748.1643317803222,488.3855594248168,239.73811236478022,477.77139894622366),c(1095.053884432888,882.6459019423052,837.8216137379688,365.05167967388104),c(677.6105244611563,316.11865300951774,613.8557456077136,819.3636446598709),c(1078.8853035889126,1609.008424868669,348.88204246769334,193.96946615900578),c(1437.533824128006,1095.759600600407,320.4920028455483,161.35513114111984),c(845.1758168441753,660.6524658401157,541.3034221288985,640.8430740356532),c(551.2016196809839,740.570102836904,1103.42620664737,622.5332719203489),c(601.1772331987264,900.4053768304803,735.6174710982467,754.1349746240991))
targetgene="AHCTF1"
-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
# set up color using RColorBrewer
#library(RColorBrewer)
@@ -361,7 +361,7 @@
# Do not modify the variables beginning with "__"
targetmat=list(c(487.9971672908978,367.6211301852257,312.2904358435953,441.15179471561487),c(358.6485205390935,394.2603425174884,593.0363832181406,268.35303725242983),c(1743.266989177725,1980.1814500315297,837.1907239685878,281.5132075228048),c(1597.7497615819454,1465.1566782744503,1065.57282048451,992.7345834391593),c(119.05954985109253,378.2768151181308,185.48159219801417,128.7407961232339),c(986.2834314825072,745.8979453033566,328.0626800781203,302.11173490252224),c(523.2740709504807,694.3954681276485,336.89513684945433,597.9294753279087),c(1562.4728579223624,763.6574201915316,422.0652557158894,220.28980669975581),c(30.8672907021351,179.37069637056908,238.47633282601822,184.81456510135357),c(339.5401977234861,447.5387671820139,310.3977665354523,205.98527379717427))
targetgene="ABT1"
-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
# set up color using RColorBrewer
#library(RColorBrewer)
@@ -396,7 +396,7 @@
# Do not modify the variables beginning with "__"
targetmat=list(c(492.4067802483456,221.99343610218943,309.7668767660713,102.99263689858714),c(243.9985836454489,239.7529109903646,130.59418226186713,174.51530141149487),c(734.9354929079785,673.0840982618383,620.7955330709046,470.9052231529845),c(1074.4756906314647,950.1319065173708,1100.902647569846,743.8357109342404),c(702.5983312200275,1010.5141211371663,1291.4313579229083,1017.3383800315995),c(1647.7253750996879,760.1055252138966,685.7771793171477,608.2287390177673),c(951.0065278229242,864.8864270541301,606.9159581445226,769.0116888427839),c(435.0818118015233,435.1071347602913,275.69882921949727,339.8757017653375),c(89.66213013477338,209.56180368046682,208.8245136651112,304.4004601669353),c(1328.7633711776252,1571.7135276035012,1122.983789498181,1356.6419004808338))
targetgene="ADIRF"
-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
# set up color using RColorBrewer
#library(RColorBrewer)
@@ -431,7 +431,7 @@
# Do not modify the variables beginning with "__"
targetmat=list(c(216.0710349149457,289.479440677255,192.42137966120518,498.36992632594104),c(1127.391046120839,1198.764554951823,371.5940741654094,370.2013115188104),c(1111.2224652768637,1038.9292809582466,948.227323379644,922.3562815584581),c(1164.137820766238,1204.0923974182756,1686.9992433247955,2089.033985093009),c(48.505742531926586,248.63264843445216,665.5887066969557,248.8988725049189),c(501.2260061632414,387.1565525622184,436.5757204116524,314.69972385679404),c(1975.5066049366465,1797.2588586833258,1628.3264947723626,1289.6966864967521),c(213.13129294331378,376.5008676293133,404.4003421732214,482.921030791153),c(2012.2533795820452,1989.0611874756173,1064.3110409457481,431.9968936579627),c(264.57677744687226,353.4135502746856,442.25372833608145,191.6807408945927))
targetgene="ABCF1"
-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
# set up color using RColorBrewer
#library(RColorBrewer)
@@ -471,7 +471,7 @@
# outputfile='__OUTPUT_FILE__'
targetgenelist=c("ACRC","AGAP3","ADCK4","AHRR","ADRBK1","ADK","ADCK1","ADARB2","ACSS2","ADNP")
# samplelabel=sub('.\\w+.\\w+$','',colnames(gstable)[startindex]);
-samplelabel='HL60.final,KBM7.final_vs_HL60.initial,KBM7.initial pos.'
+samplelabel='HL60_final,KBM7_final_vs_HL60_initial,KBM7_initial pos.'
# You need to write some codes in front of this code:
@@ -577,7 +577,7 @@
# Do not modify the variables beginning with "__"
targetmat=list(c(461.5394895462105,502.5931393353569,445.40817718298644,889.1697652244688),c(76.43329126242978,90.5733219296933,447.30084649112945,357.0411412484354),c(258.6972935036084,685.515730683561,533.7327448963265,560.7376897811967),c(232.23961575892122,681.9638357059259,275.69882921949727,467.47213525636494),c(1393.4376945535273,1472.2604682297203,1039.706339939889,532.7008052921368),c(2395.88970688001,2441.927797124084,2462.9936596634266,2461.5240218762324),c(495.34652221997754,605.5980936867728,1159.575396122279,1617.5565806239213),c(682.0201374186041,822.2636873225097,1572.1773052974536,1333.7546478367033),c(961.2956247236359,1097.5355480892247,959.5833392285019,905.1908420753603),c(1940.2297012770634,1289.3378768815162,942.5493154552149,1103.737758763192))
targetgene="ACRC"
-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
# set up color using RColorBrewer
#library(RColorBrewer)
@@ -612,7 +612,7 @@
# Do not modify the variables beginning with "__"
targetmat=list(c(1387.5582106102636,1120.6228654438523,1214.4628060584262,1111.1761158725344),c(388.0459402554127,509.69692929062694,933.0859689144999,750.1297054113762),c(326.3113588511425,635.7892009966705,960.8451187672639,615.6670961271097),c(1328.7633711776252,1038.9292809582466,1346.3187678590552,1596.3858719281006),c(352.7690365958297,234.42506852391205,310.3977665354523,429.1359870774464),c(693.7791053051318,678.4119407282909,784.1959833405838,895.4637597016048),c(837.8264619150956,719.2587329710938,374.74852301231437,993.8789460713658),c(365.99787546817333,369.3970776740432,333.74068800254935,746.6966175147567),c(707.0079441774753,635.7892009966705,837.1907239685878,1465.3563505404536),c(486.5272963050818,673.0840982618383,784.8268731099647,734.6808098765882))
targetgene="AGAP3"
-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
# set up color using RColorBrewer
#library(RColorBrewer)
@@ -647,7 +647,7 @@
# Do not modify the variables beginning with "__"
targetmat=list(c(830.4771069860158,864.8864270541301,1349.4732167059603,740.974804353724),c(1481.6299537024847,1994.38902994207,2044.082852794442,1810.9538654668238),c(1234.6916280854039,1299.9935618144214,1357.6747837079133,2232.6514954349277),c(224.89026082984142,188.25043381465665,700.2876440129107,81.24974688666317),c(812.8386551562243,845.3510046771374,946.334654071501,999.6007592323984),c(1978.4463469082782,1751.0842239740703,2659.2003779409174,2851.1794981425537),c(565.9003295391435,776.0890526132542,878.1985589783528,445.72924524444096),c(680.5502664327881,534.5601941340722,550.7667686696135,1025.9210997731484),c(161.68580843975528,333.87812789769293,275.0679394501163,465.18340999195186),c(2523.768482645998,2445.4796921017187,2153.226782897355,1516.8526689897471))
targetgene="ADCK4"
-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
# set up color using RColorBrewer
#library(RColorBrewer)
@@ -682,7 +682,7 @@
# Do not modify the variables beginning with "__"
targetmat=list(c(345.4196816667499,163.38716897121142,474.42910657451245,481.2044868428432),c(415.9734889859159,372.9489726516783,212.6098522813972,349.03060282298975),c(1.469870985815957,83.46953197442323,0.0,62.9399447713588),c(351.29916561001374,150.9555365494888,288.9475143764983,416.54799812317464),c(561.4907165816957,170.49095892648148,199.3611671243962,411.97054759434855),c(251.34793857452865,221.99343610218943,1564.6066280648815,1502.5481360871656),c(736.4053638937945,893.3015868752103,1114.782222496228,459.46159683091923),c(338.07032673767014,607.3740411755903,378.5338616286004,65.22867003577186),c(1230.2820151279561,525.6804566899846,837.1907239685878,945.2435342025885))
targetgene="AHRR"
-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
# set up color using RColorBrewer
#library(RColorBrewer)
@@ -717,7 +717,7 @@
# Do not modify the variables beginning with "__"
targetmat=list(c(371.87735941143717,877.3180594758527,2395.4884543396593,1564.9158995424211),c(1109.7525942910477,1138.3823403320275,970.308465307979,999.0285779162951),c(1462.5216308868773,1209.420239884728,1537.4783679814984,1519.14139425416),c(586.4785233405669,987.4268037825386,743.8190381001997,1312.0117578247794),c(1018.6205931704583,717.4827854822763,1070.619938639558,1144.3626322065236),c(1269.9685317449869,1212.9721348623632,1591.1039983788835,1624.9949377332637),c(1321.4140162485455,1795.4829111945082,1478.8056194290655,1237.056005415252),c(908.3802692342615,832.9193722554148,1639.6825106212207,1268.5259778009315),c(923.078979092421,758.3295777250792,1479.4365091984464,1275.964334910274),c(680.5502664327881,634.013253507853,318.5993335374053,631.1159916618979))
targetgene="ADRBK1"
-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
# set up color using RColorBrewer
#library(RColorBrewer)
@@ -752,7 +752,7 @@
# Do not modify the variables beginning with "__"
targetmat=list(c(1472.810727787589,1829.225913482041,1263.0413183007631,1315.444845721399),c(208.7216799858659,65.71005708624807,292.1019632234033,350.17496545519623),c(1011.2712382413785,1166.7975001531076,652.9709113093356,860.5606994193058),c(557.0811036242477,685.515730683561,875.0441101314478,1019.6271052960126),c(363.0581334965414,825.8155823001447,736.8792506370087,349.602784139093),c(1505.14788947554,451.09066215964896,653.6018010787167,991.0180394908496),c(198.43258308515422,28.41515982108025,249.83234867487624,114.43626322065236),c(438.02155377315523,74.58979453033565,254.87946682992424,231.16125170571777),c(804.0194292413286,472.4020320254591,1336.2245315489592,1203.2973077651598),c(454.19013461713075,490.1615069136343,896.4943622904019,685.4732166917076))
targetgene="ADK"
-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
# set up color using RColorBrewer
#library(RColorBrewer)
@@ -787,7 +787,7 @@
# Do not modify the variables beginning with "__"
targetmat=list(c(662.9118146029966,1008.7381736483488,1101.533537339227,1694.8010582978616),c(1547.7741480642028,1965.9738701209897,1869.9572764452857,2353.9539344488194),c(1459.5818889152454,1179.2291325748304,1296.4784760779562,1222.1792911965672),c(1193.5352404825571,1355.0479339677643,1622.0175970785526,1905.9359639399652),c(868.6937526172306,701.4992580829187,720.4761166331027,603.6512884889412),c(798.1399452980647,768.9852626579842,1478.8056194290655,1756.0244591209105),c(1168.5474337236858,907.5091667857504,879.4603385171149,977.8578692204745),c(809.8989131845924,687.2916781723785,678.8373918539567,865.7103312642352),c(1246.4505959719315,753.0017352586266,1301.5255942330043,1264.5207085882087),c(826.0674940285679,797.4004224790644,977.8791425405509,2066.7189137649816))
targetgene="ADCK1"
-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
# set up color using RColorBrewer
#library(RColorBrewer)
@@ -822,7 +822,7 @@
# Do not modify the variables beginning with "__"
targetmat=list(c(1863.7964100146337,1585.9211075140413,1761.4442361117538,1464.211987908247),c(742.2848478370584,598.4943037315028,943.8110949939769,820.5080072920774),c(1568.3523418656262,2083.1864043829455,1810.6536381234716,1887.6261618246608),c(1018.6205931704583,513.248824268262,679.4682816233377,824.5132765048003),c(1140.6198849931827,1191.6607649965529,880.0912282864958,977.8578692204745),c(135.22813069506805,118.98848175077354,351.40560154521734,399.95473995618005),c(665.8515565746286,701.4992580829187,986.7115993118849,746.6966175147567),c(418.9132309575478,300.1351256101601,376.6411923204574,645.4205245644794),c(561.4907165816957,543.4399315781598,881.9838975946388,580.7640358448108),c(442.4311667306031,229.0972260574595,395.5678854018874,651.142337725512))
targetgene="ADARB2"
-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
# set up color using RColorBrewer
#library(RColorBrewer)
@@ -857,7 +857,7 @@
# Do not modify the variables beginning with "__"
targetmat=list(c(734.9354929079785,358.74139274113816,541.9343118982795,378.7840312603593),c(595.2977492554626,591.3905137762326,1061.787481868224,887.4532212761591),c(1655.0747300287676,943.0281165621008,1069.358159100796,2038.1098479598186),c(626.1650399575977,884.4218494311227,517.3296108924205,858.2719741548927),c(680.5502664327881,747.673892792174,533.1018551269456,1016.194017399393),c(662.9118146029966,777.8650001020718,864.9498738213518,787.3214909580882),c(880.4527205037583,621.5816210861304,671.8976043907657,1040.7978139918332),c(94.07174309222125,447.5387671820139,711.6436598617687,927.5059134033875),c(399.80490814194036,806.280159923152,1147.58849050404,1059.1076161071376),c(698.1887182625796,531.0082991564371,504.0809257354195,347.8862401907832))
targetgene="ACSS2"
-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
# set up color using RColorBrewer
#library(RColorBrewer)
@@ -892,7 +892,7 @@
# Do not modify the variables beginning with "__"
targetmat=list(c(408.62413405683606,523.9045092011671,483.89245311522745,701.494293542599),c(1805.0015705819953,1434.9655709645526,1712.2348341000356,2152.546111180471),c(3017.64513388016,2642.609863360463,1834.6274493599499,3573.2723190648703),c(1649.1952460855039,783.1928425685244,773.4708572611067,1332.0381038883936),c(959.82575373782,1397.6706736993847,1429.5962174173474,2811.126806015325),c(495.34652221997754,301.9110730989776,336.89513684945433,555.015876620164),c(1491.9190506031964,1331.9606166131366,2087.614246881731,1983.1804416139055),c(429.2023278582595,889.7496918975753,567.8007924429005,1132.9190058844583),c(427.7324568724435,573.6310388880576,655.4944703868597,899.4690289143276),c(690.8393633334998,767.2093151691668,1040.33722970927,993.3067647552625))
targetgene="ADNP"
-collabel=c("HL60.initial","KBM7.initial","HL60.final","KBM7.final")
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
# set up color using RColorBrewer
#library(RColorBrewer)
diff -r 93f268840b0c -r 9cd937788131 test-data/out.test.log.txt
--- a/test-data/out.test.log.txt Sat Feb 17 10:41:41 2018 -0500
+++ b/test-data/out.test.log.txt Wed Apr 04 11:03:44 2018 -0400
@@ -1,112 +1,109 @@
-INFO @ Mon, 12 Feb 2018 03:40:01: Parameters: /home/maria/miniconda3/envs/mulled-v1-b1e6893952d2d7e4d51a13d040adcd7bea052bfdc57a24d59056014db875e749/bin/mageck test -k /tmp/tmp0xS0Jl/files/000/dataset_21.dat -t HL60.final,KBM7.final -c HL60.initial,KBM7.initial -n output --normcounts-to-file --pdf-report --norm-method median --gene-test-fdr-threshold 0.25 --adjust-method fdr --sort-criteria neg --remove-zero none --gene-lfc-method median
-INFO @ Mon, 12 Feb 2018 03:40:01: Welcome to MAGeCK v0.5.7. Command: test
-INFO @ Mon, 12 Feb 2018 03:40:01: Loading count table from /tmp/tmp0xS0Jl/files/000/dataset_21.dat
-INFO @ Mon, 12 Feb 2018 03:40:01: Processing 1 lines..
-DEBUG @ Mon, 12 Feb 2018 03:40:01: Parsing error in line 1 (usually the header line). Skip this line.
-INFO @ Mon, 12 Feb 2018 03:40:01: Loaded 999 records.
-INFO @ Mon, 12 Feb 2018 03:40:01: Loading R template file: /home/maria/miniconda3/envs/mulled-v1-b1e6893952d2d7e4d51a13d040adcd7bea052bfdc57a24d59056014db875e749/lib/python3.6/site-packages/mageck/plot_template.RTemplate.
-INFO @ Mon, 12 Feb 2018 03:40:01: Loading R template file: /home/maria/miniconda3/envs/mulled-v1-b1e6893952d2d7e4d51a13d040adcd7bea052bfdc57a24d59056014db875e749/lib/python3.6/site-packages/mageck/plot_template_indvgene.RTemplate.
-INFO @ Mon, 12 Feb 2018 03:40:01: Loading Rnw template file: /home/maria/miniconda3/envs/mulled-v1-b1e6893952d2d7e4d51a13d040adcd7bea052bfdc57a24d59056014db875e749/lib/python3.6/site-packages/mageck/plot_template.Rnw.
-DEBUG @ Mon, 12 Feb 2018 03:40:01: Setting up the visualization module...
-DEBUG @ Mon, 12 Feb 2018 03:40:01: Given sample labels: HL60.final,KBM7.final
-DEBUG @ Mon, 12 Feb 2018 03:40:01: Converted index: 2 3
-INFO @ Mon, 12 Feb 2018 03:40:01: Treatment samples:HL60.final,KBM7.final
-INFO @ Mon, 12 Feb 2018 03:40:01: Treatment sample index:2,3
-DEBUG @ Mon, 12 Feb 2018 03:40:01: Given sample labels: HL60.initial,KBM7.initial
-DEBUG @ Mon, 12 Feb 2018 03:40:01: Converted index: 0 1
-INFO @ Mon, 12 Feb 2018 03:40:01: Control samples:HL60.initial,KBM7.initial
-INFO @ Mon, 12 Feb 2018 03:40:01: Control sample index:0,1
-DEBUG @ Mon, 12 Feb 2018 03:40:01: Initial (total) size factor: 1.6666455325878438 2.027372749328462 0.7198064117880387 0.6589869375844738
-DEBUG @ Mon, 12 Feb 2018 03:40:01: Median factor: 1.469870985815957 1.7759474888175155 0.6308897693810006 0.5721813161032618
-INFO @ Mon, 12 Feb 2018 03:40:01: Final size factor: 1.469870985815957 1.7759474888175155 0.6308897693810006 0.5721813161032618
-INFO @ Mon, 12 Feb 2018 03:40:01: Writing normalized read counts to output.normalized.txt
-DEBUG @ Mon, 12 Feb 2018 03:40:01: Adjusted model: 1.1175084644498339 3.4299551007579927
-INFO @ Mon, 12 Feb 2018 03:40:01: Raw variance calculation: 0.5 for control, 0.5 for treatment
-INFO @ Mon, 12 Feb 2018 03:40:01: Adjusted variance calculation: 0.3333333333333333 for raw variance, 0.6666666666666667 for modeling
-INFO @ Mon, 12 Feb 2018 03:40:01: Use qnorm to reversely calculate sgRNA scores ...
-DEBUG @ Mon, 12 Feb 2018 03:40:01: lower test FDR cutoff: 0.3283283283283283
-DEBUG @ Mon, 12 Feb 2018 03:40:01: higher test FDR cutoff: 0.34534534534534533
-INFO @ Mon, 12 Feb 2018 03:40:01: Running command: RRA -i output.plow.txt -o output.gene.low.txt -p 0.3283283283283283 --skip-gene NA --skip-gene na
-INFO @ Mon, 12 Feb 2018 03:40:02: Command message:
-INFO @ Mon, 12 Feb 2018 03:40:02: Welcome to RRA v 0.5.7.
-INFO @ Mon, 12 Feb 2018 03:40:02: Skipping gene NA for permutation ...
-INFO @ Mon, 12 Feb 2018 03:40:02: Skipping gene na for permutation ...
-INFO @ Mon, 12 Feb 2018 03:40:02: Reading input file...
-INFO @ Mon, 12 Feb 2018 03:40:02: Summary: 999 sgRNAs, 100 genes, 1 lists; skipped sgRNAs:0
-INFO @ Mon, 12 Feb 2018 03:40:02: Computing lo-values for each group...
-INFO @ Mon, 12 Feb 2018 03:40:02: Computing false discovery rate...
-INFO @ Mon, 12 Feb 2018 03:40:02: Increase the number of permutations to 1001 to get precise p values. To avoid this, use the --permutation option.
-INFO @ Mon, 12 Feb 2018 03:40:02: Permuting genes with 9 sgRNAs...
-INFO @ Mon, 12 Feb 2018 03:40:02: Permuting genes with 10 sgRNAs...
-INFO @ Mon, 12 Feb 2018 03:40:02: Number of genes under FDR adjustment: 100
-INFO @ Mon, 12 Feb 2018 03:40:02: Saving to output file...
-INFO @ Mon, 12 Feb 2018 03:40:02: RRA completed.
-INFO @ Mon, 12 Feb 2018 03:40:02:
-INFO @ Mon, 12 Feb 2018 03:40:02: End command message.
-INFO @ Mon, 12 Feb 2018 03:40:02: Running command: RRA -i output.phigh.txt -o output.gene.high.txt -p 0.34534534534534533 --skip-gene NA --skip-gene na
-INFO @ Mon, 12 Feb 2018 03:40:03: Command message:
-INFO @ Mon, 12 Feb 2018 03:40:03: Welcome to RRA v 0.5.7.
-INFO @ Mon, 12 Feb 2018 03:40:03: Skipping gene NA for permutation ...
-INFO @ Mon, 12 Feb 2018 03:40:03: Skipping gene na for permutation ...
-INFO @ Mon, 12 Feb 2018 03:40:03: Reading input file...
-INFO @ Mon, 12 Feb 2018 03:40:03: Summary: 999 sgRNAs, 100 genes, 1 lists; skipped sgRNAs:0
-INFO @ Mon, 12 Feb 2018 03:40:03: Computing lo-values for each group...
-INFO @ Mon, 12 Feb 2018 03:40:03: Computing false discovery rate...
-INFO @ Mon, 12 Feb 2018 03:40:03: Increase the number of permutations to 1001 to get precise p values. To avoid this, use the --permutation option.
-INFO @ Mon, 12 Feb 2018 03:40:03: Permuting genes with 9 sgRNAs...
-INFO @ Mon, 12 Feb 2018 03:40:03: Permuting genes with 10 sgRNAs...
-INFO @ Mon, 12 Feb 2018 03:40:03: Number of genes under FDR adjustment: 100
-INFO @ Mon, 12 Feb 2018 03:40:03: Saving to output file...
-INFO @ Mon, 12 Feb 2018 03:40:03: RRA completed.
-INFO @ Mon, 12 Feb 2018 03:40:03:
-INFO @ Mon, 12 Feb 2018 03:40:03: End command message.
-DEBUG @ Mon, 12 Feb 2018 03:40:03: Sorting the merged items by negative selection...
-INFO @ Mon, 12 Feb 2018 03:40:03: Loading top 10 genes from output.gene.low.txt: ACIN1,ACTR8,AHCY,ACLY,AATF,AGBL5,AHCTF1,ABT1,ADIRF,ABCF1
-DEBUG @ Mon, 12 Feb 2018 03:40:03: Column index:3
-INFO @ Mon, 12 Feb 2018 03:40:03: Loading top 10 genes from output.gene.high.txt: ACRC,AGAP3,ADCK4,AHRR,ADRBK1,ADK,ADCK1,ADARB2,ACSS2,ADNP
-DEBUG @ Mon, 12 Feb 2018 03:40:03: Column index:9
-INFO @ Mon, 12 Feb 2018 03:40:03: Running command: rm output.plow.txt
-INFO @ Mon, 12 Feb 2018 03:40:03: Running command: rm output.phigh.txt
-INFO @ Mon, 12 Feb 2018 03:40:03: Running command: rm output.gene.low.txt
-INFO @ Mon, 12 Feb 2018 03:40:03: Running command: rm output.gene.high.txt
-INFO @ Mon, 12 Feb 2018 03:40:03: Running command: cd ./; Rscript output.R
-INFO @ Mon, 12 Feb 2018 03:40:04: Command message:
-INFO @ Mon, 12 Feb 2018 03:40:04: null device
-INFO @ Mon, 12 Feb 2018 03:40:04: 1
-INFO @ Mon, 12 Feb 2018 03:40:04: Writing to file output_summary.tex
-INFO @ Mon, 12 Feb 2018 03:40:04: Processing code chunks with options ...
-INFO @ Mon, 12 Feb 2018 03:40:04: 1 : keep.source term verbatim (label = funcdef, output_summary.Rnw:27)
-INFO @ Mon, 12 Feb 2018 03:40:04: 2 : keep.source term tex (label = tab1, output_summary.Rnw:37)
-INFO @ Mon, 12 Feb 2018 03:40:04: 3 : keep.source term verbatim (output_summary.Rnw:77)
-INFO @ Mon, 12 Feb 2018 03:40:04: 4 : keep.source term verbatim pdf (output_summary.Rnw:83)
-INFO @ Mon, 12 Feb 2018 03:40:04: 5 : keep.source term verbatim pdf (output_summary.Rnw:201)
-INFO @ Mon, 12 Feb 2018 03:40:04: 6 : keep.source term verbatim pdf (output_summary.Rnw:345)
-INFO @ Mon, 12 Feb 2018 03:40:04: 7 : keep.source term verbatim pdf (output_summary.Rnw:489)
-INFO @ Mon, 12 Feb 2018 03:40:04: 8 : keep.source term verbatim (output_summary.Rnw:567)
-INFO @ Mon, 12 Feb 2018 03:40:04: 9 : keep.source term verbatim pdf (output_summary.Rnw:573)
-INFO @ Mon, 12 Feb 2018 03:40:04: 10 : keep.source term verbatim pdf (output_summary.Rnw:691)
-INFO @ Mon, 12 Feb 2018 03:40:04: 11 : keep.source term verbatim pdf (output_summary.Rnw:835)
-INFO @ Mon, 12 Feb 2018 03:40:04: 12 : keep.source term verbatim pdf (output_summary.Rnw:979)
-INFO @ Mon, 12 Feb 2018 03:40:04:
-INFO @ Mon, 12 Feb 2018 03:40:04: You can now run (pdf)latex on ‘output_summary.tex’
-INFO @ Mon, 12 Feb 2018 03:40:04: Error in texi2dvi("output_summary.tex", pdf = TRUE) :
-INFO @ Mon, 12 Feb 2018 03:40:04: pdflatex is not available
-INFO @ Mon, 12 Feb 2018 03:40:04: Execution halted
-INFO @ Mon, 12 Feb 2018 03:40:04:
-INFO @ Mon, 12 Feb 2018 03:40:04: End command message.
-INFO @ Mon, 12 Feb 2018 03:40:04: Running command: cd ./; rm -rf output_summary-*.pdf
-INFO @ Mon, 12 Feb 2018 03:40:04: Command message:
-INFO @ Mon, 12 Feb 2018 03:40:04:
-INFO @ Mon, 12 Feb 2018 03:40:04: End command message.
-INFO @ Mon, 12 Feb 2018 03:40:04: Running command: cd ./; rm -rf output_summary.aux
-INFO @ Mon, 12 Feb 2018 03:40:04: Command message:
-INFO @ Mon, 12 Feb 2018 03:40:04:
-INFO @ Mon, 12 Feb 2018 03:40:04: End command message.
-INFO @ Mon, 12 Feb 2018 03:40:04: Running command: cd ./; rm -rf output_summary.tex
-INFO @ Mon, 12 Feb 2018 03:40:04: Command message:
-INFO @ Mon, 12 Feb 2018 03:40:04:
-INFO @ Mon, 12 Feb 2018 03:40:04: End command message.
-INFO @ Mon, 12 Feb 2018 03:40:04: Running command: cd ./; rm -rf output_summary.toc
-INFO @ Mon, 12 Feb 2018 03:40:04: Command message:
-INFO @ Mon, 12 Feb 2018 03:40:04:
-INFO @ Mon, 12 Feb 2018 03:40:04: End command message.
+INFO @ Mon, 26 Mar 2018 08:37:53: Parameters: /Users/doylemaria/miniconda3/envs/mulled-v1-9ee130591ca78526e74a59d8d6dc03cb7db20645470975762936caeac62972dc/bin/mageck test -k /private/var/folders/zn/m_qvr9zd7tq0wdtsbq255f8xypj_zg/T/tmpTX65kA/files/000/dataset_4.dat -t HL60_final,KBM7_final -c HL60_initial,KBM7_initial -n output --normcounts-to-file --pdf-report --norm-method median --adjust-method fdr --sort-criteria neg --remove-zero both --gene-lfc-method median
+INFO @ Mon, 26 Mar 2018 08:37:53: Welcome to MAGeCK v0.5.7. Command: test
+INFO @ Mon, 26 Mar 2018 08:37:53: Loading count table from /private/var/folders/zn/m_qvr9zd7tq0wdtsbq255f8xypj_zg/T/tmpTX65kA/files/000/dataset_4.dat
+INFO @ Mon, 26 Mar 2018 08:37:53: Processing 1 lines..
+DEBUG @ Mon, 26 Mar 2018 08:37:53: Parsing error in line 1 (usually the header line). Skip this line.
+INFO @ Mon, 26 Mar 2018 08:37:53: Loaded 999 records.
+INFO @ Mon, 26 Mar 2018 08:37:53: Loading R template file: /Users/doylemaria/miniconda3/envs/mulled-v1-9ee130591ca78526e74a59d8d6dc03cb7db20645470975762936caeac62972dc/lib/python3.6/site-packages/mageck/plot_template.RTemplate.
+INFO @ Mon, 26 Mar 2018 08:37:53: Loading R template file: /Users/doylemaria/miniconda3/envs/mulled-v1-9ee130591ca78526e74a59d8d6dc03cb7db20645470975762936caeac62972dc/lib/python3.6/site-packages/mageck/plot_template_indvgene.RTemplate.
+INFO @ Mon, 26 Mar 2018 08:37:53: Loading Rnw template file: /Users/doylemaria/miniconda3/envs/mulled-v1-9ee130591ca78526e74a59d8d6dc03cb7db20645470975762936caeac62972dc/lib/python3.6/site-packages/mageck/plot_template.Rnw.
+DEBUG @ Mon, 26 Mar 2018 08:37:53: Setting up the visualization module...
+DEBUG @ Mon, 26 Mar 2018 08:37:53: Given sample labels: HL60_final,KBM7_final
+DEBUG @ Mon, 26 Mar 2018 08:37:53: Converted index: 2 3
+INFO @ Mon, 26 Mar 2018 08:37:53: Treatment samples:HL60_final,KBM7_final
+INFO @ Mon, 26 Mar 2018 08:37:53: Treatment sample index:2,3
+DEBUG @ Mon, 26 Mar 2018 08:37:53: Given sample labels: HL60_initial,KBM7_initial
+DEBUG @ Mon, 26 Mar 2018 08:37:53: Converted index: 0 1
+INFO @ Mon, 26 Mar 2018 08:37:53: Control samples:HL60_initial,KBM7_initial
+INFO @ Mon, 26 Mar 2018 08:37:53: Control sample index:0,1
+DEBUG @ Mon, 26 Mar 2018 08:37:53: Initial (total) size factor: 1.6666455325878438 2.027372749328462 0.7198064117880387 0.6589869375844738
+DEBUG @ Mon, 26 Mar 2018 08:37:53: Median factor: 1.469870985815957 1.7759474888175155 0.6308897693810006 0.5721813161032618
+INFO @ Mon, 26 Mar 2018 08:37:53: Final size factor: 1.469870985815957 1.7759474888175155 0.6308897693810006 0.5721813161032618
+INFO @ Mon, 26 Mar 2018 08:37:53: Writing normalized read counts to output.normalized.txt
+DEBUG @ Mon, 26 Mar 2018 08:37:53: Adjusted model: 1.1175084644498339 3.4299551007579927
+INFO @ Mon, 26 Mar 2018 08:37:53: Raw variance calculation: 0.5 for control, 0.5 for treatment
+INFO @ Mon, 26 Mar 2018 08:37:53: Adjusted variance calculation: 0.3333333333333333 for raw variance, 0.6666666666666667 for modeling
+INFO @ Mon, 26 Mar 2018 08:37:53: Use qnorm to reversely calculate sgRNA scores ...
+DEBUG @ Mon, 26 Mar 2018 08:37:53: lower test FDR cutoff: 0.3283283283283283
+DEBUG @ Mon, 26 Mar 2018 08:37:53: higher test FDR cutoff: 0.34534534534534533
+INFO @ Mon, 26 Mar 2018 08:37:53: Running command: RRA -i output.plow.txt -o output.gene.low.txt -p 0.3283283283283283 --skip-gene NA --skip-gene na
+INFO @ Mon, 26 Mar 2018 08:37:53: Command message:
+INFO @ Mon, 26 Mar 2018 08:37:53: Welcome to RRA v 0.5.7.
+INFO @ Mon, 26 Mar 2018 08:37:53: Skipping gene NA for permutation ...
+INFO @ Mon, 26 Mar 2018 08:37:53: Skipping gene na for permutation ...
+INFO @ Mon, 26 Mar 2018 08:37:53: Reading input file...
+INFO @ Mon, 26 Mar 2018 08:37:53: Summary: 999 sgRNAs, 100 genes, 1 lists; skipped sgRNAs:0
+INFO @ Mon, 26 Mar 2018 08:37:53: Computing lo-values for each group...
+INFO @ Mon, 26 Mar 2018 08:37:53: Computing false discovery rate...
+INFO @ Mon, 26 Mar 2018 08:37:53: Increase the number of permutations to 1001 to get precise p values. To avoid this, use the --permutation option.
+INFO @ Mon, 26 Mar 2018 08:37:53: Permuting genes with 9 sgRNAs...
+INFO @ Mon, 26 Mar 2018 08:37:53: Permuting genes with 10 sgRNAs...
+INFO @ Mon, 26 Mar 2018 08:37:53: Number of genes under FDR adjustment: 100
+INFO @ Mon, 26 Mar 2018 08:37:53: Saving to output file...
+INFO @ Mon, 26 Mar 2018 08:37:53: RRA completed.
+INFO @ Mon, 26 Mar 2018 08:37:53:
+INFO @ Mon, 26 Mar 2018 08:37:53: End command message.
+INFO @ Mon, 26 Mar 2018 08:37:53: Running command: RRA -i output.phigh.txt -o output.gene.high.txt -p 0.34534534534534533 --skip-gene NA --skip-gene na
+INFO @ Mon, 26 Mar 2018 08:37:53: Command message:
+INFO @ Mon, 26 Mar 2018 08:37:53: Welcome to RRA v 0.5.7.
+INFO @ Mon, 26 Mar 2018 08:37:53: Skipping gene NA for permutation ...
+INFO @ Mon, 26 Mar 2018 08:37:53: Skipping gene na for permutation ...
+INFO @ Mon, 26 Mar 2018 08:37:53: Reading input file...
+INFO @ Mon, 26 Mar 2018 08:37:53: Summary: 999 sgRNAs, 100 genes, 1 lists; skipped sgRNAs:0
+INFO @ Mon, 26 Mar 2018 08:37:53: Computing lo-values for each group...
+INFO @ Mon, 26 Mar 2018 08:37:53: Computing false discovery rate...
+INFO @ Mon, 26 Mar 2018 08:37:53: Increase the number of permutations to 1001 to get precise p values. To avoid this, use the --permutation option.
+INFO @ Mon, 26 Mar 2018 08:37:53: Permuting genes with 9 sgRNAs...
+INFO @ Mon, 26 Mar 2018 08:37:53: Permuting genes with 10 sgRNAs...
+INFO @ Mon, 26 Mar 2018 08:37:53: Number of genes under FDR adjustment: 100
+INFO @ Mon, 26 Mar 2018 08:37:53: Saving to output file...
+INFO @ Mon, 26 Mar 2018 08:37:53: RRA completed.
+INFO @ Mon, 26 Mar 2018 08:37:53:
+INFO @ Mon, 26 Mar 2018 08:37:53: End command message.
+DEBUG @ Mon, 26 Mar 2018 08:37:53: Sorting the merged items by negative selection...
+INFO @ Mon, 26 Mar 2018 08:37:53: Loading top 10 genes from output.gene.low.txt: ACIN1,ACTR8,AHCY,ACLY,AATF,AGBL5,AHCTF1,ABT1,ADIRF,ABCF1
+DEBUG @ Mon, 26 Mar 2018 08:37:53: Column index:3
+INFO @ Mon, 26 Mar 2018 08:37:53: Loading top 10 genes from output.gene.high.txt: ACRC,AGAP3,ADCK4,AHRR,ADRBK1,ADK,ADCK1,ADARB2,ACSS2,ADNP
+DEBUG @ Mon, 26 Mar 2018 08:37:53: Column index:9
+INFO @ Mon, 26 Mar 2018 08:37:53: Running command: rm output.plow.txt
+INFO @ Mon, 26 Mar 2018 08:37:53: Running command: rm output.phigh.txt
+INFO @ Mon, 26 Mar 2018 08:37:54: Running command: rm output.gene.low.txt
+INFO @ Mon, 26 Mar 2018 08:37:54: Running command: rm output.gene.high.txt
+INFO @ Mon, 26 Mar 2018 08:37:54: Running command: cd ./; Rscript output.R
+INFO @ Mon, 26 Mar 2018 08:37:59: Command message:
+INFO @ Mon, 26 Mar 2018 08:37:59: null device
+INFO @ Mon, 26 Mar 2018 08:37:59: 1
+INFO @ Mon, 26 Mar 2018 08:37:59: Writing to file output_summary.tex
+INFO @ Mon, 26 Mar 2018 08:37:59: Processing code chunks with options ...
+INFO @ Mon, 26 Mar 2018 08:37:59: 1 : keep.source term verbatim (label = funcdef, output_summary.Rnw:27)
+INFO @ Mon, 26 Mar 2018 08:37:59: 2 : keep.source term tex (label = tab1, output_summary.Rnw:37)
+INFO @ Mon, 26 Mar 2018 08:37:59: 3 : keep.source term verbatim (output_summary.Rnw:77)
+INFO @ Mon, 26 Mar 2018 08:37:59: 4 : keep.source term verbatim pdf (output_summary.Rnw:83)
+INFO @ Mon, 26 Mar 2018 08:37:59: 5 : keep.source term verbatim pdf (output_summary.Rnw:201)
+INFO @ Mon, 26 Mar 2018 08:37:59: 6 : keep.source term verbatim pdf (output_summary.Rnw:345)
+INFO @ Mon, 26 Mar 2018 08:37:59: 7 : keep.source term verbatim pdf (output_summary.Rnw:489)
+INFO @ Mon, 26 Mar 2018 08:37:59: 8 : keep.source term verbatim (output_summary.Rnw:567)
+INFO @ Mon, 26 Mar 2018 08:37:59: 9 : keep.source term verbatim pdf (output_summary.Rnw:573)
+INFO @ Mon, 26 Mar 2018 08:37:59: 10 : keep.source term verbatim pdf (output_summary.Rnw:691)
+INFO @ Mon, 26 Mar 2018 08:37:59: 11 : keep.source term verbatim pdf (output_summary.Rnw:835)
+INFO @ Mon, 26 Mar 2018 08:37:59: 12 : keep.source term verbatim pdf (output_summary.Rnw:979)
+INFO @ Mon, 26 Mar 2018 08:37:59:
+INFO @ Mon, 26 Mar 2018 08:37:59: You can now run (pdf)latex on ‘output_summary.tex’
+INFO @ Mon, 26 Mar 2018 08:37:59:
+INFO @ Mon, 26 Mar 2018 08:37:59: End command message.
+INFO @ Mon, 26 Mar 2018 08:37:59: Running command: cd ./; rm -rf output_summary-*.pdf
+INFO @ Mon, 26 Mar 2018 08:37:59: Command message:
+INFO @ Mon, 26 Mar 2018 08:37:59:
+INFO @ Mon, 26 Mar 2018 08:37:59: End command message.
+INFO @ Mon, 26 Mar 2018 08:37:59: Running command: cd ./; rm -rf output_summary.aux
+INFO @ Mon, 26 Mar 2018 08:37:59: Command message:
+INFO @ Mon, 26 Mar 2018 08:37:59:
+INFO @ Mon, 26 Mar 2018 08:37:59: End command message.
+INFO @ Mon, 26 Mar 2018 08:37:59: Running command: cd ./; rm -rf output_summary.tex
+INFO @ Mon, 26 Mar 2018 08:37:59: Command message:
+INFO @ Mon, 26 Mar 2018 08:37:59:
+INFO @ Mon, 26 Mar 2018 08:37:59: End command message.
+INFO @ Mon, 26 Mar 2018 08:37:59: Running command: cd ./; rm -rf output_summary.toc
+INFO @ Mon, 26 Mar 2018 08:37:59: Command message:
+INFO @ Mon, 26 Mar 2018 08:37:59:
+INFO @ Mon, 26 Mar 2018 08:37:59: End command message.
diff -r 93f268840b0c -r 9cd937788131 test-data/out.test.normalized.txt
--- a/test-data/out.test.normalized.txt Sat Feb 17 10:41:41 2018 -0500
+++ b/test-data/out.test.normalized.txt Wed Apr 04 11:03:44 2018 -0400
@@ -1,4 +1,4 @@
-sgRNA Gene HL60.initial KBM7.initial HL60.final KBM7.final
+sgRNA Gene HL60_initial KBM7_initial HL60_final KBM7_final
A1CF_m52595977 A1CF 313.08251997879887 486.6096119359992 557.0756663634236 100.13173031807082
A1CF_m52596017 A1CF 432.1420698298914 731.6903653928164 980.402701618075 1081.994868751268
A1CF_m52596056 A1CF 618.8156850285179 653.5486758848457 357.0836094696463 434.28561892237576
diff -r 93f268840b0c -r 9cd937788131 test-data/out.test.pdf
Binary file test-data/out.test.pdf has changed
diff -r 93f268840b0c -r 9cd937788131 test-data/out.test.plots.pdf
Binary file test-data/out.test.plots.pdf has changed
diff -r 93f268840b0c -r 9cd937788131 test-data/out.test.report.pdf
Binary file test-data/out.test.report.pdf has changed
diff -r 93f268840b0c -r 9cd937788131 test-data/output.count_normalized.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output.count_normalized.txt Wed Apr 04 11:03:44 2018 -0400
@@ -0,0 +1,2551 @@
+sgRNA Gene test1_fastq_gz
+s_47512 RNF111 2.0
+s_24835 HCFC1R1 2.0
+s_14784 CYP4B1 8.0
+s_51146 SLC18A1 2.0
+s_58960 TRIM5 2.0
+s_48256 RPRD2 2.0
+s_30297 KRTAP5-5 2.0
+s_14555 CYB5B 2.0
+s_39959 PAAF1 2.0
+s_45293 PUF60 2.0
+s_49358 SCN8A 2.0
+s_64995 ZYG11A 2.0
+s_4029 ASTE1 2.0
+s_45554 R3HDML 2.0
+s_34264 MMRN1 2.0
+s_37459 NOL6 2.0
+s_23990 GPX7 2.0
+s_20268 FANCC 2.0
+s_14157 CTLA4 2.0
+s_36773 NEURL4 36.0
+s_18804 ETFB 2.0
+s_782 ACSS1 2.0
+s_18272 ENPP2 2.0
+s_46620 RCN1 2.0
+s_55436 TAS2R3 2.0
+s_57947 TMPRSS2 2.0
+s_6438 C14orf159 2.0
+s_33846 MGST2 2.0
+s_16328 DNAH6 2.0
+s_17875 EIF4G1 2.0
+s_2305 ANAPC11 2.0
+s_2500 ANKRD2 2.0
+s_82 AARSD1 2.0
+s_55329 TAL1 2.0
+s_57926 TMPRSS11E 16.0
+s_38414 NUP98 8.0
+s_50044 SERPINF1 2.0
+s_9257 CASR 2.0
+s_63396 ZNF182 2.0
+s_56478 THBS3 2.0
+s_17191 DYRK1A 2.0
+s_11988 CIR1 2.0
+s_43313 PPARD 2.0
+s_44681 PSMA4 2.0
+s_10387 CD320 2.0
+s_64869 ZPBP 2.0
+s_54385 STK17B 2.0
+s_25423 HIST1H4D 2.0
+s_54172 ST8SIA4 18.0
+s_1161 ADCY10 2.0
+s_29184 KIAA0913 2.0
+s_42977 POLD3 2.0
+s_49449 SCUBE1 2.0
+s_24181 GRM4 2.0
+s_52507 SMARCA5 2.0
+s_28674 KCNJ10 2.0
+s_61074 VAMP2 8.0
+s_3954 ASIC2 2.0
+s_2385 ANK1 2.0
+s_18397 EPDR1 2.0
+s_18377 EPB41L4B 2.0
+s_34580 MRAP2 2.0
+s_48676 RUFY3 20.0
+s_691 ACP1 2.0
+s_30460 LAMP2 2.0
+s_42637 PLRG1 2.0
+s_12695 CNOT6 2.0
+s_33316 MECOM 4.0
+s_35081 MSRB2 2.0
+s_58512 TPD52L2 2.0
+s_19912 FAM22F 2.0
+s_45517 QSOX2 2.0
+s_56705 TINAG 2.0
+s_10946 CDKL5 2.0
+s_57473 TMEM211 4.0
+s_57657 TMEM44 2.0
+s_43200 POT1 2.0
+s_19436 FAM135A 2.0
+s_184 ABCB9 2.0
+s_30171 KRT84 2.0
+s_44758 PSMC3IP 2.0
+s_48313 RPS3 2.0
+s_58142 TNFSF12 12.0
+s_59718 TTLL6 14.0
+s_9725 CCDC43 2.0
+s_5135 BCKDHA 2.0
+s_36539 NDUFC2 2.0
+s_27251 IL27RA 2.0
+s_48939 SAMD10 2.0
+s_27343 IL5RA 2.0
+s_28386 KANK2 2.0
+s_27610 INSRR 2.0
+s_2769 AOC3 4.0
+s_58632 TRA2B 24.0
+s_6674 C16orf86 2.0
+s_22902 GJD4 2.0
+s_48278 RPS15A 2.0
+s_61998 WIPF2 2.0
+s_4937 BAIAP3 4.0
+s_54471 STOML1 4.0
+s_19157 FABP12 2.0
+s_5434 BIN1 4.0
+s_42042 PIP5K1A 2.0
+s_7794 C3orf18 2.0
+s_54846 SVIL 2.0
+s_62273 XPA 2.0
+s_45859 RACGAP1 2.0
+s_53626 SPOCK3 2.0
+s_43295 PPAP2C 14.0
+s_11788 CHRDL1 4.0
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+s_45566 RAB11FIP1 0
+s_45586 RAB11FIP5 0
+s_45600 RAB15 0
+s_45601 RAB15 0
+s_45604 RAB17 0
+s_45627 RAB24 0
+s_45707 RAB3C 0
+s_45729 RAB3IP 0
+s_45763 RAB6A 0
+s_45796 RAB9B 0
+s_45894 RAD51AP1 0
+s_45908 RAD51C 0
+s_45960 RAI14 0
+s_45961 RAI14 0
+s_46068 RAP1GDS1 0
+s_46107 RAPH1 0
+s_46265 RASSF4 0
+s_46298 RAVER2 0
+s_46321 RBBP5 0
+s_46328 RBBP7 0
+s_46355 RBFOX3 0
+s_46452 RBM39 0
+s_46581 RCAN1 0
+s_46634 RCOR2 0
+s_46639 RCSD1 0
+s_46646 RD3 0
+s_46657 RDH10 0
+s_46672 RDH13 0
+s_46717 REEP1 0
+s_46821 RERG 0
+s_46827 RERGL 0
+s_46848 RETNLB 0
+s_46976 RFXANK 0
+s_47005 RGL2 0
+s_4703 AXIN1 0
+s_47100 RGS3 0
+s_47144 RHAG 0
+s_47186 RHD 0
+s_47216 RHOC 0
+s_47394 RIPPLY1 0
+s_47413 RLBP1 0
+s_47554 RNF130 0
+s_47584 RNF144A 0
+s_47594 RNF145 0
+s_47622 RNF165 0
+s_47710 RNF215 0
+s_47777 RNF44 0
+s_47780 RNF6 0
+s_47786 RNF7 0
+s_47791 RNF8 0
+s_47915 RP11-178D12.1 0
+s_47946 RP11-428C6.1 0
+s_47969 RP11-6F2.7 0
+s_47970 RP11-6F2.7 0
+s_48013 RP4-697K14.7 0
+s_48066 RPAP3 0
+s_48073 RPE 0
+s_48097 RPH3AL 0
+s_48098 RPH3AL 0
+s_48179 RPL36 0
+s_48201 RPL6 0
+s_4837 B4GALT5 0
+s_48399 RPUSD2 0
+s_4841 B4GALT6 0
+s_48414 RQCD1 0
+s_4843 B4GALT7 0
+s_48438 RREB1 0
+s_48461 RRNAD1 0
+s_48488 RRS1 0
+s_48512 RSC1A1 0
+s_4868 BACE1 0
+s_48714 RUSC1 0
+s_48860 S100B 0
+s_48874 S100Z 0
+s_48933 SALL3 0
+s_4898 BAG4 0
+s_49069 SASS6 0
+s_49192 SCARB1 0
+s_49246 SCGB1D1 0
+s_4925 BAIAP2 0
+s_49278 SCIN 0
+s_49297 SCML1 0
+s_49354 SCN7A 0
+s_49570 SDR9C7 0
+s_49599 SEC14L2 0
+s_49625 SEC22A 0
+s_49651 SEC24D 0
+s_49668 SEC61A2 0
+s_49706 SELE 0
+s_4972 BARHL2 0
+s_49775 SEMA4F 0
+s_49799 SEMA6D 0
+s_49844 SEPP1 0
+s_49859 12-Sep 0
+s_49881 5-Sep 0
+s_49934 SERINC5 0
+s_49957 SERPINA3 0
+s_50004 SERPINB5 0
+s_5001 BAX 0
+s_5006 BAZ1A 0
+s_50112 SETD3 0
+s_50123 SETD6 0
+s_50127 SETD7 0
+s_50162 SEZ6L2 0
+s_5022 BAZ2B 0
+s_5026 BBC3 0
+s_50280 SGCA 0
+s_50284 SGCB 0
+s_50342 SGPP2 0
+s_50388 SH2D3C 0
+s_50391 SH2D3C 0
+s_50491 SH3KBP1 0
+s_505 ACACB 0
+s_50517 SH3TC2 0
+s_5056 BBS4 0
+s_50560 SHE 0
+s_50596 SHISA6 0
+s_50652 SI 0
+s_50684 SIGLEC1 0
+s_50692 SIGLEC10 0
+s_50693 SIGLEC11 0
+s_50722 SIGLEC9 0
+s_50761 SIPA1 0
+s_50779 SIRPB1 0
+s_50780 SIRPB1 0
+s_51043 SLC15A1 0
+s_51096 SLC16A5 0
+s_51179 SLC1A2 0
+s_51276 SLC22A5 0
+s_51312 SLC24A4 0
+s_51344 SLC25A13 0
+s_51482 SLC25A5 0
+s_51528 SLC26A9 0
+s_51555 SLC28A1 0
+s_51613 SLC2A6 0
+s_51660 SLC30A6 0
+s_51715 SLC35A4 0
+s_51729 SLC35B3 0
+s_51774 SLC35F3 0
+s_51783 SLC35G2 0
+s_51872 SLC39A14 0
+s_51904 SLC39A8 0
+s_52017 SLC4A2 0
+s_52093 SLC5A5 0
+s_52206 SLC7A14 0
+s_52255 SLC8A2 0
+s_52313 SLC9B1 0
+s_52364 SLCO4C1 0
+s_52383 SLFN13 0
+s_52421 SLITRK4 0
+s_52435 SLMO1 0
+s_52485 SMAP1 0
+s_5253 BCO2 0
+s_52574 SMCR8 0
+s_52587 SMG5 0
+s_52601 SMG7 0
+s_52617 SMO 0
+s_52642 SMPD4 0
+s_5268 BDH1 0
+s_52758 SNAPIN 0
+s_52784 SNIP1 0
+s_52787 SNIP1 0
+s_52833 SNRPB2 0
+s_52989 SNX8 0
+s_53 AAK1 0
+s_53048 SON 0
+s_53055 SORBS1 0
+s_53109 SOSTDC1 0
+s_53151 SOX30 0
+s_53153 SOX30 0
+s_53181 SP100 0
+s_53438 SPDYC 0
+s_53476 SPERT 0
+s_53512 SPI1 0
+s_53525 SPIN1 0
+s_53535 SPINK1 0
+s_53555 SPINK6 0
+s_53574 SPINT1 0
+s_53639 SPP1 0
+s_53691 SPRR3 0
+s_53740 SPTA1 0
+s_53830 SREK1 0
+s_53993 SSBP1 0
+s_54019 SSPN 0
+s_54054 SSTR5 0
+s_54078 ST14 0
+s_54092 ST3GAL3 0
+s_54099 ST3GAL3 0
+s_54292 STAT5A 0
+s_54305 STATH 0
+s_54314 STAU2 0
+s_54327 STC2 0
+s_5437 BIN2 0
+s_54380 STK17A 0
+s_54403 STK3 0
+s_54480 STON1 0
+s_54588 STX5 0
+s_54609 STXBP4 0
+s_54639 SUCLG1 0
+s_54645 SUCNR1 0
+s_54679 SULT1B1 0
+s_54684 SULT1C3 0
+s_54704 SULT2B1 0
+s_54758 SUPT4H1 0
+s_54772 SUPV3L1 0
+s_54801 SUSD4 0
+s_54866 SWT1 0
+s_5492 BLOC1S3 0
+s_54942 SYNDIG1 0
+s_5503 BMF 0
+s_55131 SZT2 0
+s_55147 TAAR8 0
+s_55187 TACO1 0
+s_55464 TAS2R8 0
+s_55509 TBC1D10C 0
+s_55520 TBC1D14 0
+s_55528 TBC1D15 0
+s_55577 TBC1D30 0
+s_55709 TBX21 0
+s_55725 TBX5 0
+s_55844 TCF4 0
+s_55845 TCF4 0
+s_55862 TCF7L2 0
+s_55868 TCHH 0
+s_5588 BNIP2 0
+s_55911 TCP10L2 0
+s_55913 TCP11 0
+s_55922 TCP11L2 0
+s_55946 TCTN1 0
+s_56006 TEAD2 0
+s_56014 TEAD4 0
+s_56080 TEN1 0
+s_56099 TERF1 0
+s_56118 TES 0
+s_56167 TEX13B 0
+s_5618 BOK 0
+s_56207 TEX9 0
+s_56284 TFEC 0
+s_56297 TFG 0
+s_56361 TGFBR2 0
+s_56373 TGIF1 0
+s_56415 TGS1 0
+s_56492 THEM4 0
+s_56509 THNSL1 0
+s_5655 BPIFA1 0
+s_56621 TIFA 0
+s_56646 TIMD4 0
+s_56684 TIMM8B 0
+s_56805 TLL1 0
+s_56819 TLR10 0
+s_56826 TLR3 0
+s_56873 TM4SF18 0
+s_57016 TMED10 0
+s_57082 TMEM106C 0
+s_57087 TMEM107 0
+s_57150 TMEM127 0
+s_57173 TMEM132B 0
+s_57181 TMEM132E 0
+s_57189 TMEM134 0
+s_57288 TMEM164 0
+s_57299 TMEM167B 0
+s_57409 TMEM194A 0
+s_57422 TMEM198 0
+s_57429 TMEM2 0
+s_57475 TMEM212 0
+s_57531 TMEM231 0
+s_57568 TMEM245 0
+s_57700 TMEM54 0
+s_57873 TMF1 0
+s_57992 TMUB1 0
+s_58180 TNIP1 0
+s_58211 TNKS2 0
+s_58237 TNNT1 0
+s_58256 TNPO2 0
+s_58259 TNPO3 0
+s_58309 TOM1 0
+s_58485 TP73 0
+s_58503 TPD52 0
+s_58533 TPI1 0
+s_5857 BSPRY 0
+s_58612 TPSG1 0
+s_58633 TRA2B 0
+s_58655 TRAF3 0
+s_58668 TRAF3IP2 0
+s_58690 TRAK1 0
+s_58809 TRIB2 0
+s_58962 TRIM50 0
+s_58968 TRIM52 0
+s_59050 TRIO 0
+s_59107 TRMT1L 0
+s_59133 TRMT61B 0
+s_59160 TROVE2 0
+s_59173 TRPC4 0
+s_59196 TRPM1 0
+s_59204 TRPM3 0
+s_59311 TSEN54 0
+s_59332 TSHB 0
+s_59340 TSHZ2 0
+s_59360 TSNARE1 0
+s_5952 BTG4 0
+s_59539 TTC21A 0
+s_59602 TTC39A 0
+s_59654 TTC9C 0
+s_59717 TTLL6 0
+s_5974 BTN3A1 0
+s_59748 TTYH1 0
+s_59807 TUBB2B 0
+s_59859 TULP1 0
+s_59870 TULP3 0
+s_59955 TXNDC8 0
+s_59983 TXNRD2 0
+s_600 ACE 0
+s_60169 UBE2H 0
+s_60209 UBE2Q2 0
+s_60237 UBE2V2 0
+s_60248 UBE3A 0
+s_60250 UBE3B 0
+s_60373 UBXN6 0
+s_60396 UCKL1 0
+s_60423 UEVLD 0
+s_60438 UFSP1 0
+s_60449 UGDH 0
+s_60517 UGT2A1 0
+s_60542 UGT3A1 0
+s_60603 UMODL1 0
+s_60614 UNC119 0
+s_60649 UNC5B 0
+s_6068 C10orf125 0
+s_6071 C10orf128 0
+s_60753 UQCRC2 0
+s_60780 URM1 0
+s_60839 USP15 0
+s_60851 USP19 0
+s_60925 USP4 0
+s_6100 C10orf53 0
+s_6106 C10orf54 0
+s_61149 VAV2 0
+s_61173 VCAM1 0
+s_61178 VCAN 0
+s_61221 VEPH1 0
+s_61263 VIL1 0
+s_61341 VPS13C 0
+s_61344 VPS13D 0
+s_61367 VPS29 0
+s_61529 VWA5A 0
+s_61531 VWA5A 0
+s_61587 WBP1 0
+s_61595 WBP2 0
+s_61623 WDFY1 0
+s_61640 WDHD1 0
+s_61662 WDR16 0
+s_61695 WDR26 0
+s_61739 WDR44 0
+s_6200 C11orf49 0
+s_62019 WISP1 0
+s_62098 WNT5B 0
+s_62114 WNT8A 0
+s_62171 WTAP 0
+s_62249 XKR3 0
+s_62257 XKR6 0
+s_62275 XPC 0
+s_62320 XRCC4 0
+s_62361 YAE1D1 0
+s_62550 ZBBX 0
+s_62559 ZBED6 0
+s_62567 ZBTB1 0
+s_62624 ZBTB37 0
+s_62657 ZBTB47 0
+s_62759 ZC3H7A 0
+s_62845 ZDHHC11 0
+s_62862 ZDHHC16 0
+s_62881 ZDHHC2 0
+s_6292 C12orf23 0
+s_62975 ZFC3H1 0
+s_63034 ZFP64 0
+s_63104 ZFYVE27 0
+s_63107 ZFYVE27 0
+s_63114 ZFYVE28 0
+s_63217 ZMIZ2 0
+s_63228 ZMYM3 0
+s_63234 ZMYM3 0
+s_6326 C12orf49 0
+s_63302 ZNF132 0
+s_63362 ZNF167 0
+s_63435 ZNF200 0
+s_63487 ZNF223 0
+s_63594 ZNF276 0
+s_636 ACO1 0
+s_63746 ZNF354B 0
+s_63755 ZNF362 0
+s_6376 C12orf74 0
+s_63903 ZNF436 0
+s_63905 ZNF438 0
+s_63923 ZNF442 0
+s_63934 ZNF445 0
+s_63935 ZNF446 0
+s_63964 ZNF469 0
+s_63983 ZNF480 0
+s_6409 C14orf105 0
+s_64137 ZNF554 0
+s_64241 ZNF586 0
+s_6427 C14orf133 0
+s_64356 ZNF639 0
+s_64393 ZNF655 0
+s_64396 ZNF655 0
+s_64419 ZNF668 0
+s_64424 ZNF669 0
+s_64459 ZNF682 0
+s_64479 ZNF688 0
+s_64581 ZNF746 0
+s_64627 ZNF772 0
+s_64638 ZNF776 0
+s_64652 ZNF780A 0
+s_64791 ZNF85 0
+s_64851 ZNRF3 0
+s_64871 ZPBP 0
+s_64878 ZPLD1 0
+s_64898 ZSCAN10 0
+s_64930 ZSCAN30 0
+s_64997 ZYG11A 0
+s_6525 C15orf39 0
+s_6592 C16orf13 0
+s_6639 C16orf62 0
+s_6707 C17orf102 0
+s_6710 C17orf104 0
+s_6728 C17orf112 0
+s_6736 C17orf39 0
+s_6794 C17orf72 0
+s_6814 C17orf80 0
+s_6849 C18orf21 0
+s_6859 C18orf32 0
+s_6862 C18orf34 0
+s_6906 C19orf38 0
+s_7053 C1QTNF7 0
+s_7128 C1orf122 0
+s_7144 C1orf130 0
+s_7162 C1orf144 0
+s_7234 C1orf198 0
+s_7341 C1orf63 0
+s_747 ACSL1 0
+s_76 AARS2 0
+s_7674 C2orf57 0
+s_7681 C2orf62 0
+s_7692 C2orf63 0
+s_77 AARSD1 0
+s_78 AARSD1 0
+s_781 ACSS1 0
+s_786 ACSS2 0
+s_7940 C4orf26 0
+s_7970 C4orf37 0
+s_8000 C4orf52 0
+s_804 ACTB 0
+s_8073 C5orf51 0
+s_8141 C6orf162 0
+s_8227 C7orf10 0
+s_8281 C7orf59 0
+s_8318 C8A 0
+s_8403 C9orf100 0
+s_8470 C9orf24 0
+s_8699 CACNA1G 0
+s_8705 CACNA1I 0
+s_871 ACTR8 0
+s_874 ACTR8 0
+s_8757 CACNG5 0
+s_8797 CADPS 0
+s_8879 CALR 0
+s_8910 CAMK2B 0
+s_893 ACVR1B 0
+s_8930 CAMKK1 0
+s_8954 CAMSAP1 0
+s_9064 CAPRIN1 0
+s_9077 CAPSL 0
+s_9109 CARD17 0
+s_913 ACY1 0
+s_9171 CASD1 0
+s_9196 CASP10 0
+s_9285 CATSPER3 0
+s_9506 CCDC120 0
+s_9507 CCDC121 0
+s_952 ADAM12 0
+s_9584 CCDC149 0
+s_964 ADAM18 0
+s_9646 CCDC170 0
+s_9710 CCDC40 0
+s_9732 CCDC48 0
+s_976 ADAM21 0
+s_9763 CCDC62 0
+s_9868 CCDC89 0
+s_991 ADAM30 0
+s_9925 CCL1 0
+s_9973 CCL26 0
diff -r 93f268840b0c -r 9cd937788131 test-data/output_countsummary.Rnw
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output_countsummary.Rnw Wed Apr 04 11:03:44 2018 -0400
@@ -0,0 +1,237 @@
+% This is a template file for Sweave used in MAGeCK
+% Author: Wei Li, Shirley Liu lab
+% Do not modify lines beginning with "#__".
+\documentclass{article}
+
+\usepackage{amsmath}
+\usepackage{amscd}
+\usepackage[tableposition=top]{caption}
+\usepackage{ifthen}
+\usepackage{fullpage}
+\usepackage[utf8]{inputenc}
+% \usepackage{longtable}
+
+\begin{document}
+\setkeys{Gin}{width=0.9\textwidth}
+
+\title{MAGeCK Count Report}
+\author{Wei Li}
+
+\maketitle
+
+
+\tableofcontents
+
+\section{Summary}
+
+%Function definition
+<>=
+genreporttable<-function(filelist,labellist,reads,mappedreads){
+ xtb=data.frame(Label=labellist,Reads=reads,MappedReads=mappedreads,MappedPercentage=mappedreads/reads);
+ colnames(xtb)=c("Label","Reads","Mapped","Percentage");
+ return (xtb);
+}
+genreporttable2<-function(filelist,labellist,sgrnas,zerocounts,gini){
+ xtb=data.frame(Label=labellist,TotalsgRNAs=sgrnas,ZeroCounts=zerocounts,GiniIndex=gini);
+ colnames(xtb)=c("Label","TotalsgRNA","ZeroCounts","GiniIndex");
+ return (xtb);
+}
+genreporttable3<-function(filelist,labellist){
+ xtb=data.frame(File=filelist,Label=labellist);
+ colnames(xtb)=c("File","Label");
+ return (xtb);
+}
+
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F");
+
+
+
+genboxplot<-function(filename,...){
+ #slmed=read.table(filename,header=T)
+ slmed=read.table(filename,header=T)
+ slmat=as.matrix(slmed[,c(-1,-2)])
+ slmat_log=log2(slmat+1)
+
+ boxplot(slmat_log,pch='.',las=2,ylab='log2(read counts)',cex.axis=0.8,...)
+}
+
+
+genhistplot<-function(filename,isfile=T,...){
+ if(isfile){
+ slmed=read.table(filename,header=T)
+ }else{
+ slmed=filename;
+ }
+ tabsmat=as.matrix(log2(slmed[,c(-1,-2)]+1))
+ colnames(tabsmat)=colnames(slmed)[c(-1,-2)]
+ samplecol=colors[((1:ncol(tabsmat)) %% length(colors)) ]
+ if(ncol(tabsmat)>=1){
+ histlist=lapply(1:ncol(tabsmat),function(X){ return (hist(tabsmat[,X],plot=F,breaks=40)) })
+ xrange=range(unlist(lapply(histlist,function(X){X$mids})))
+ yrange=range(unlist(lapply(histlist,function(X){X$counts})))
+ hst1=histlist[[1]]
+ plot(hst1$mids,hst1$counts,type='b',pch=20,xlim=c(0,xrange[2]*1.2),ylim=c(0,yrange[2]*1.2),xlab='log2(counts)',ylab='Frequency',main='Distribution of read counts',col = samplecol[1], ... )
+ }
+ if(ncol(tabsmat)>=2){
+ for(i in 2:ncol(tabsmat)){
+ hstn=histlist[[i]]
+ lines(hstn$mids,hstn$counts,type='b',pch=20,col=samplecol[i])
+ }
+ }
+ legend('topright',colnames(tabsmat),pch=20,lwd=1,col=samplecol)
+}
+
+
+
+genclustering<-function(filename,...){
+ #slmed=read.table(filename,header=T)
+ slmed=read.table(filename,header=T)
+ slmat=as.matrix(slmed[,c(-1,-2)])
+ slmat_log=log2(slmat+1)
+
+ result=tryCatch({
+ library(gplots);
+ heatmap.2(cor(slmat_log),trace = 'none',density.info = 'none',cexRow = 0.8,cexCol = 0.8,offsetRow = -0.2,offsetCol = -0.2)
+ }, error=function(e){
+ heatmap(cor(slmat_log),scale='none',cexRow = 0.8,cexCol = 0.8,cex.axis=0.8,...)
+ });
+}
+
+ctfit_tx=0;
+
+
+panel.plot<-function(x,y,textnames=names(x),...){
+ par(new=TRUE)
+ m<-cbind(x,y)
+ plot(m,pch=20,xlim = range(x)*1.1,ylim=range(y)*1.1,...)
+ text(x,y,textnames,...)
+}
+
+
+genpcaplot<-function(filename,...){
+ #slmed=read.table(filename,header=T)
+ slmed=read.table(filename,header=T)
+ slmat=as.matrix(slmed[,c(-1,-2)])
+ slmat_log=log2(slmat+1)
+ ctfit_tx<<-prcomp(t(slmat_log),center=TRUE)
+
+ # par(mfrow=c(2,1));
+ samplecol=colors[((1:ncol(slmat)) %% length(colors)) ]
+ # first 2 PCA
+ #plot(ctfit_tx$x[,1],ctfit_tx$x[,2],xlab='PC1',ylab='PC2',main='First 2 PCs',col=samplecol,xlim=1.1*range(ctfit_tx$x[,1]),ylim=1.1*range(ctfit_tx$x[,2]));
+ #text(ctfit_tx$x[,1],ctfit_tx$x[,2],rownames(ctfit_tx$x),col=samplecol);
+ # par(mfrow=c(1,1));
+ if(length(samplecol)>2){
+ pairs(ctfit_tx$x[,1:3],panel=panel.plot,textnames=rownames(ctfit_tx$x),main='First 3 principle components',col=samplecol)
+ }else{
+ if(length(samplecol)>1){
+ pairs(ctfit_tx$x[,1:2],panel=panel.plot,textnames=rownames(ctfit_tx$x),main='First 2 principle components',col=samplecol)
+ }
+ }
+
+
+}
+
+genpcavar<-function(){
+ # % variance
+ varpca=ctfit_tx$sdev^2
+ varpca=varpca/sum(varpca)*100;
+ if(length(varpca)>10){
+ varpca=varpca[1:10];
+ }
+ plot(varpca,type='b',lwd=2,pch=20,xlab='PCs',ylab='% Variance explained');
+}
+
+@
+
+%__FILE_SUMMARY__
+
+The statistics of comparisons are listed in Table 1 and Table 2.
+The corresponding fastq files in each row are listed in Table 3.
+
+<>=
+library(xtable)
+filelist=c("input_0.gz");
+labellist=c("test1_fastq_gz");
+reads=c(2500);
+mappedreads=c(1453);
+totalsgrnas=c(2550);
+zerocounts=c(1276);
+giniindex=c(0.5266899931488773);
+
+cptable=genreporttable(filelist,labellist,reads,mappedreads);
+print(xtable(cptable, caption = "Summary of comparisons", label = "tab:one",
+ digits = c(0, 0, 0, 0,2),
+ align=c('c', 'c','c', 'c', 'c'),
+ table.placement = "tbp",
+ caption.placement = "top"))
+@
+
+<>=
+library(xtable)
+cptable=genreporttable2(filelist,labellist,totalsgrnas,zerocounts,giniindex);
+print(xtable(cptable, caption = "Summary of comparisons", label = "tab:two",
+ digits = c(0, 0,0, 0,2),
+ align=c('c', 'c','c', 'c', 'c'),
+ table.placement = "tbp",
+ caption.placement = "top"))
+@
+
+
+
+
+
+<>=
+library(xtable)
+cptable=genreporttable3(filelist,labellist);
+print(xtable(cptable, caption = "Summary of samples", label = "tab:three",
+ digits = c(0,0, 0),
+ align=c('c', 'p{9cm}', 'c'),
+ table.placement = "tbp",
+ caption.placement = "top"))
+@
+
+
+
+
+The meanings of the columns are as follows.
+
+\begin{itemize}
+\item \textbf{Row}: The row number in the table;
+\item \textbf{File}: The filename of fastq file;
+\item \textbf{Label}: Assigned label;
+\item \textbf{Reads}: The total read count in the fastq file;
+\item \textbf{Mapped}: Reads that can be mapped to gRNA library;
+\item \textbf{Percentage}: The percentage of mapped reads;
+\item \textbf{TotalsgRNAs}: The number of sgRNAs in the library;
+\item \textbf{ZeroCounts}: The number of sgRNA with 0 read counts;
+\item \textbf{GiniIndex}: The Gini Index of the read count distribution. Gini index can be used to measure the evenness of the read counts, and a smaller value means a more even distribution of the read counts.
+\end{itemize}
+
+
+
+\newpage\section{Normalized read count distribution of all samples}
+The following figure shows the distribution of median-normalized read counts in all samples.
+
+
+<>=
+genboxplot("output.count_normalized.txt");
+@
+
+The following figure shows the histogram of median-normalized read counts in all samples.
+
+
+<>=
+genhistplot("output.count_normalized.txt");
+@
+
+%__INDIVIDUAL_PAGE__
+
+
+
+\end{document}
+
diff -r 93f268840b0c -r 9cd937788131 test-data/output_summary.Rnw
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output_summary.Rnw Wed Apr 04 11:03:44 2018 -0400
@@ -0,0 +1,1063 @@
+% This is a template file for Sweave used in MAGeCK
+% Author: Wei Li, Shirley Liu lab
+% Do not modify lines beginning with "#__".
+\documentclass{article}
+
+\usepackage{amsmath}
+\usepackage{amscd}
+\usepackage[tableposition=top]{caption}
+\usepackage{ifthen}
+\usepackage{fullpage}
+\usepackage[utf8]{inputenc}
+
+\begin{document}
+\setkeys{Gin}{width=0.9\textwidth}
+
+\title{MAGeCK Comparison Report}
+\author{Wei Li}
+
+\maketitle
+
+
+\tableofcontents
+
+\section{Summary}
+
+%Function definition
+<>=
+genreporttable<-function(comparisons,ngenes,direction,fdr1,fdr5,fdr25){
+ xtb=data.frame(Comparison=comparisons,Genes=ngenes,Selection=direction,FDR1=fdr1,FDR5=fdr5,FDR25=fdr25);
+ colnames(xtb)=c("Comparison","Genes","Selection","FDR1%","FDR5%","FDR25%");
+ return (xtb);
+}
+@
+
+The statistics of comparisons is as indicated in the following table.
+
+<>=
+library(xtable)
+comparisons=c("HL60_final,KBM7_final_vs_HL60_initial,KBM7_initial neg.","HL60_final,KBM7_final_vs_HL60_initial,KBM7_initial pos.");
+ngenes=c(100,100);
+direction=c("negative","positive");
+fdr1=c(0,0);
+fdr5=c(2,0);
+fdr25=c(9,1);
+
+cptable=genreporttable(comparisons,ngenes,direction,fdr1,fdr5,fdr25);
+print(xtable(cptable, caption = "Summary of comparisons", label = "tab:one",
+ digits = c(0, 0, 0, 0, 0, 0, 0),
+ table.placement = "tbp",
+ caption.placement = "top"))
+@
+
+The meanings of the columns are as follows.
+
+\begin{itemize}
+\item \textbf{Comparison}: The label for comparisons;
+\item \textbf{Genes}: The number of genes in the library;
+\item \textbf{Selection}: The direction of selection, either positive selection or negative selection;
+\item \textbf{FDR1\%}: The number of genes with FDR $<$ 1\%;
+\item \textbf{FDR5\%}: The number of genes with FDR $<$ 5\%;
+\item \textbf{FDR25\%}: The number of genes with FDR $<$ 25\%;
+\end{itemize}
+
+The following figures show:
+
+\begin{itemize}
+\item Individual sgRNA read counts of selected genes in selected samples;
+\item The distribution of RRA scores and p values of all genes; and
+\item The RRA scores and p values of selected genes.
+\end{itemize}
+
+
+\newpage\section{Comparison results of HL60 final,KBM7 final vs HL60 initial,KBM7 initial neg.}
+
+The following figure shows the distribution of RRA score in the comparison HL60 final,KBM7 final vs HL60 initial,KBM7 initial neg., and the RRA scores of 10 genes.
+
+<>=
+gstable=read.table('output.gene_summary.txt',header=T)
+@
+%
+
+
+<>=#
+#
+# parameters
+# Do not modify the variables beginning with "__"
+
+# gstablename='__GENE_SUMMARY_FILE__'
+startindex=3
+# outputfile='__OUTPUT_FILE__'
+targetgenelist=c("ACIN1","ACTR8","AHCY","ACLY","AATF","AGBL5","AHCTF1","ABT1","ADIRF","ABCF1")
+# samplelabel=sub('.\w+.\w+$','',colnames(gstable)[startindex]);
+samplelabel='HL60_final,KBM7_final_vs_HL60_initial,KBM7_initial neg.'
+
+
+# You need to write some codes in front of this code:
+# gstable=read.table(gstablename,header=T)
+# pdf(file=outputfile,width=6,height=6)
+
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+######
+# function definition
+
+plotrankedvalues<-function(val, tglist, ...){
+
+ plot(val,log='y',ylim=c(max(val),min(val)),type='l',lwd=2, ...)
+ if(length(tglist)>0){
+ for(i in 1:length(tglist)){
+ targetgene=tglist[i];
+ tx=which(names(val)==targetgene);ty=val[targetgene];
+ points(tx,ty,col=colors[(i %% length(colors)) ],cex=2,pch=20)
+ # text(tx+50,ty,targetgene,col=colors[i])
+ }
+ legend('topright',tglist,pch=20,pt.cex = 2,cex=1,col=colors)
+ }
+}
+
+
+
+plotrandvalues<-function(val,targetgenelist, ...){
+ # choose the one with the best distance distribution
+
+ mindiffvalue=0;
+ randval=val;
+ for(i in 1:20){
+ randval0=sample(val)
+ vindex=sort(which(names(randval0) %in% targetgenelist))
+ if(max(vindex)>0.9*length(val)){
+ # print('pass...')
+ next;
+ }
+ mindiffind=min(diff(vindex));
+ if (mindiffind > mindiffvalue){
+ mindiffvalue=mindiffind;
+ randval=randval0;
+ # print(paste('Diff: ',mindiffvalue))
+ }
+ }
+ plot(randval,log='y',ylim=c(max(randval),min(randval)),pch=20,col='grey', ...)
+
+ if(length(targetgenelist)>0){
+ for(i in 1:length(targetgenelist)){
+ targetgene=targetgenelist[i];
+ tx=which(names(randval)==targetgene);ty=randval[targetgene];
+ points(tx,ty,col=colors[(i %% length(colors)) ],cex=2,pch=20)
+ text(tx+50,ty,targetgene,col=colors[i])
+ }
+ }
+
+}
+
+
+
+
+# set.seed(1235)
+
+
+
+pvec=gstable[,startindex]
+names(pvec)=gstable[,'id']
+pvec=sort(pvec);
+
+plotrankedvalues(pvec,targetgenelist,xlab='Genes',ylab='RRA score',main=paste('Distribution of RRA scores in \n',samplelabel))
+
+# plotrandvalues(pvec,targetgenelist,xlab='Genes',ylab='RRA score',main=paste('Distribution of RRA scores in \n',samplelabel))
+
+
+pvec=gstable[,startindex+1]
+names(pvec)=gstable[,'id']
+pvec=sort(pvec);
+
+plotrankedvalues(pvec,targetgenelist,xlab='Genes',ylab='p value',main=paste('Distribution of p values in \n',samplelabel))
+
+# plotrandvalues(pvec,targetgenelist,xlab='Genes',ylab='p value',main=paste('Distribution of p values in \n',samplelabel))
+
+
+
+# you need to write after this code:
+# dev.off()
+
+
+
+
+@
+%%
+\clearpage
+\newpage
+The following figures show the distribution of sgRNA read counts (normalized) of selected genes in selected samples.
+%
+
+
+<>=
+par(mfrow=c(2,2));
+
+# parameters
+# Do not modify the variables beginning with "__"
+targetmat=list(c(561.4907165816957,824.0396348113272,428.37415340969943,579.047491896501),c(3424.79939695118,3818.2871009576584,1992.3498917052,690.0506672205338),c(846.6456878299913,985.6508562937211,335.0024675413113,415.97581680707134),c(2432.636481525409,2122.257249136931,1067.465489792653,155.6333179800872),c(1308.1851773762019,2186.1913587343615,1482.5909580453515,997.3120339679854),c(405.68439208520414,268.16807081144486,170.34023773287015,109.85881269182627),c(640.8637498157573,559.4234589775174,711.6436598617687,632.2603542941043),c(946.5969148654764,470.6260845366416,663.0651476194316,457.74505288260946),c(246.9383256170808,177.59474888175154,28.39003962214503,0.0),c(568.8400715107754,612.7018836420428,564.0154538266146,270.64176251684285))
+targetgene="ACIN1"
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+
+## code
+
+targetmatvec=unlist(targetmat)+1
+yrange=range(targetmatvec[targetmatvec>0]);
+# yrange[1]=1; # set the minimum value to 1
+for(i in 1:length(targetmat)){
+ vali=targetmat[[i]]+1;
+ if(i==1){
+ plot(1:length(vali),vali,type='b',las=1,pch=20,main=paste('sgRNAs in',targetgene),ylab='Read counts',xlab='Samples',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt='n',log='y')
+ axis(1,at=1:length(vali),labels=(collabel),las=2)
+ # lines(0:100,rep(1,101),col='black');
+ }else{
+ lines(1:length(vali),vali,type='b',pch=20,col=colors[(i %% length(colors))])
+ }
+}
+
+
+
+# parameters
+# Do not modify the variables beginning with "__"
+targetmat=list(c(2484.0819660289676,2349.578527705573,2172.7843657481662,910.9126552363929),c(992.1629154257711,1005.1862786707138,743.8190381001997,200.26346063614164),c(1267.0287897733551,1156.1418152202027,251.09412821363824,42.34141739164138),c(1500.738276518092,1315.977089213779,800.5991173444897,1476.2277955464156),c(1925.5309914189038,2054.7712445618654,194.94493873872918,235.16652091844063),c(351.29916561001374,781.4168950797068,227.75120674654121,624.2498158686586),c(1719.74905340467,1006.9622261595313,356.45271970026533,222.0063506480656),c(903.9706562768137,1445.6212558974576,1482.5909580453515,1055.1023468944147),c(651.152846716469,1081.552020689867,576.0023594448536,1072.2677863775127),c(285.1549712482957,408.46792242802854,99.0496937928171,44.630142656054424))
+targetgene="ACTR8"
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+
+## code
+
+targetmatvec=unlist(targetmat)+1
+yrange=range(targetmatvec[targetmatvec>0]);
+# yrange[1]=1; # set the minimum value to 1
+for(i in 1:length(targetmat)){
+ vali=targetmat[[i]]+1;
+ if(i==1){
+ plot(1:length(vali),vali,type='b',las=1,pch=20,main=paste('sgRNAs in',targetgene),ylab='Read counts',xlab='Samples',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt='n',log='y')
+ axis(1,at=1:length(vali),labels=(collabel),las=2)
+ # lines(0:100,rep(1,101),col='black');
+ }else{
+ lines(1:length(vali),vali,type='b',pch=20,col=colors[(i %% length(colors))])
+ }
+}
+
+
+
+# parameters
+# Do not modify the variables beginning with "__"
+targetmat=list(c(301.3235520922712,657.1005708624807,228.38209651592223,137.32351586478285),c(1142.0897559789987,1099.311495578042,112.92926871919911,100.70391163417409),c(789.3207193831689,671.3081507730209,723.6305654800077,588.7745742702564),c(392.45555321286054,412.0198174056636,334.37157777193033,213.99581222261992),c(2009.3136376104133,2235.917888421252,2437.1271791188055,1937.9781176417478),c(1071.5359486598327,406.69197493921104,645.4002340767636,349.602784139093),c(61.7345814042702,218.44154112455442,614.4866353770946,452.5954210376801),c(651.152846716469,879.0940069646701,237.21455328725622,18.88198343140764),c(1625.6773103124485,1410.1023061211074,2146.286995434164,1986.613529510525),c(1053.8974968300413,882.6459019423052,106.6203710253891,105.85354347910344))
+targetgene="AHCY"
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+
+## code
+
+targetmatvec=unlist(targetmat)+1
+yrange=range(targetmatvec[targetmatvec>0]);
+# yrange[1]=1; # set the minimum value to 1
+for(i in 1:length(targetmat)){
+ vali=targetmat[[i]]+1;
+ if(i==1){
+ plot(1:length(vali),vali,type='b',las=1,pch=20,main=paste('sgRNAs in',targetgene),ylab='Read counts',xlab='Samples',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt='n',log='y')
+ axis(1,at=1:length(vali),labels=(collabel),las=2)
+ # lines(0:100,rep(1,101),col='black');
+ }else{
+ lines(1:length(vali),vali,type='b',pch=20,col=colors[(i %% length(colors))])
+ }
+}
+
+
+
+# parameters
+# Do not modify the variables beginning with "__"
+targetmat=list(c(1268.498660759171,1411.8782536099247,1136.2324746551822,603.6512884889412),c(327.78122983695846,454.642557137284,51.73296108924205,24.031615276336996),c(132.28838872343613,241.5288584791821,123.02350502929512,65.80085135187511),c(495.34652221997754,586.0626713097802,279.4841678357833,243.74924065998954),c(1009.8013672555626,1102.8633905556771,1237.174837756142,1004.7503910773278),c(877.5129785321263,715.7068379934587,538.1489732819936,594.496387431289),c(1594.8100196103135,1108.1912330221296,605.6541786057605,127.59643349102738),c(314.5523909646148,252.1845434120872,88.95545748272109,359.9020478289517),c(512.984974049769,269.94401830026237,205.67006481820619,126.45207085882086),c(761.3931706526657,475.9539270030942,559.5992254409475,596.7851126957021))
+targetgene="ACLY"
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+
+## code
+
+targetmatvec=unlist(targetmat)+1
+yrange=range(targetmatvec[targetmatvec>0]);
+# yrange[1]=1; # set the minimum value to 1
+for(i in 1:length(targetmat)){
+ vali=targetmat[[i]]+1;
+ if(i==1){
+ plot(1:length(vali),vali,type='b',las=1,pch=20,main=paste('sgRNAs in',targetgene),ylab='Read counts',xlab='Samples',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt='n',log='y')
+ axis(1,at=1:length(vali),labels=(collabel),las=2)
+ # lines(0:100,rep(1,101),col='black');
+ }else{
+ lines(1:length(vali),vali,type='b',pch=20,col=colors[(i %% length(colors))])
+ }
+}
+
+
+
+par(mfrow=c(1,1));
+@
+%
+
+
+<>=
+par(mfrow=c(2,2));
+
+# parameters
+# Do not modify the variables beginning with "__"
+targetmat=list(c(659.9720726313648,809.832054900787,880.7221180558769,802.1982051767731),c(724.6463960072668,1086.8798631563195,695.2405258578626,307.26136674745163),c(836.3565909292796,1289.3378768815162,468.75109865008346,177.94838930811443),c(367.46774645398926,571.85509139924,300.30353022535627,116.72498848506541),c(518.8644579930328,632.2373060190355,627.7353205340956,308.9779106957614),c(405.68439208520414,259.28833336735727,324.27734146183434,166.5047629860492),c(2096.0360257735547,1960.6460276545372,1573.4390848362154,629.9716290296913),c(277.8056163192159,435.1071347602913,182.32714335110919,0.0),c(995.1026573974029,477.7298744919117,728.0467938656747,275.21921304566894),c(2185.6981559083283,1482.9161531626255,1741.8866532609427,1862.4501839161173))
+targetgene="AATF"
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+
+## code
+
+targetmatvec=unlist(targetmat)+1
+yrange=range(targetmatvec[targetmatvec>0]);
+# yrange[1]=1; # set the minimum value to 1
+for(i in 1:length(targetmat)){
+ vali=targetmat[[i]]+1;
+ if(i==1){
+ plot(1:length(vali),vali,type='b',las=1,pch=20,main=paste('sgRNAs in',targetgene),ylab='Read counts',xlab='Samples',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt='n',log='y')
+ axis(1,at=1:length(vali),labels=(collabel),las=2)
+ # lines(0:100,rep(1,101),col='black');
+ }else{
+ lines(1:length(vali),vali,type='b',pch=20,col=colors[(i %% length(colors))])
+ }
+}
+
+
+
+# parameters
+# Do not modify the variables beginning with "__"
+targetmat=list(c(640.8637498157573,602.0461987091378,307.2433176885473,192.82510352679924),c(354.23890758164566,280.5997032331675,204.4082852794442,275.79139436177223),c(779.0316224824572,932.3724316291956,778.5179754161547,905.1908420753603),c(624.6951689717818,554.0956165110648,370.96318439602834,558.4489645167836),c(1133.270530064103,1394.1187787217498,639.0913363829536,1131.2024619361487),c(423.32284391499564,412.0198174056636,224.59675789963623,426.84726181303336),c(296.91393913482335,829.3674772777797,489.5704610396565,1233.0507362025292),c(684.959879390236,546.9918265557948,394.30610586312537,566.4595029422292),c(440.96129574478715,630.461358530218,434.6830511035094,457.1728715665062),c(1108.2827233052317,1969.5257650986248,1066.2037102538911,1333.7546478367033))
+targetgene="AGBL5"
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+
+## code
+
+targetmatvec=unlist(targetmat)+1
+yrange=range(targetmatvec[targetmatvec>0]);
+# yrange[1]=1; # set the minimum value to 1
+for(i in 1:length(targetmat)){
+ vali=targetmat[[i]]+1;
+ if(i==1){
+ plot(1:length(vali),vali,type='b',las=1,pch=20,main=paste('sgRNAs in',targetgene),ylab='Read counts',xlab='Samples',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt='n',log='y')
+ axis(1,at=1:length(vali),labels=(collabel),las=2)
+ # lines(0:100,rep(1,101),col='black');
+ }else{
+ lines(1:length(vali),vali,type='b',pch=20,col=colors[(i %% length(colors))])
+ }
+}
+
+
+
+# parameters
+# Do not modify the variables beginning with "__"
+targetmat=list(c(196.96271209933826,301.9110730989776,423.9579250240324,34.33087896619571),c(1106.8128523194157,1056.6887558464218,1743.1484327997048,807.3478370217025),c(748.1643317803222,488.3855594248168,239.73811236478022,477.77139894622366),c(1095.053884432888,882.6459019423052,837.8216137379688,365.05167967388104),c(677.6105244611563,316.11865300951774,613.8557456077136,819.3636446598709),c(1078.8853035889126,1609.008424868669,348.88204246769334,193.96946615900578),c(1437.533824128006,1095.759600600407,320.4920028455483,161.35513114111984),c(845.1758168441753,660.6524658401157,541.3034221288985,640.8430740356532),c(551.2016196809839,740.570102836904,1103.42620664737,622.5332719203489),c(601.1772331987264,900.4053768304803,735.6174710982467,754.1349746240991))
+targetgene="AHCTF1"
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+
+## code
+
+targetmatvec=unlist(targetmat)+1
+yrange=range(targetmatvec[targetmatvec>0]);
+# yrange[1]=1; # set the minimum value to 1
+for(i in 1:length(targetmat)){
+ vali=targetmat[[i]]+1;
+ if(i==1){
+ plot(1:length(vali),vali,type='b',las=1,pch=20,main=paste('sgRNAs in',targetgene),ylab='Read counts',xlab='Samples',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt='n',log='y')
+ axis(1,at=1:length(vali),labels=(collabel),las=2)
+ # lines(0:100,rep(1,101),col='black');
+ }else{
+ lines(1:length(vali),vali,type='b',pch=20,col=colors[(i %% length(colors))])
+ }
+}
+
+
+
+# parameters
+# Do not modify the variables beginning with "__"
+targetmat=list(c(487.9971672908978,367.6211301852257,312.2904358435953,441.15179471561487),c(358.6485205390935,394.2603425174884,593.0363832181406,268.35303725242983),c(1743.266989177725,1980.1814500315297,837.1907239685878,281.5132075228048),c(1597.7497615819454,1465.1566782744503,1065.57282048451,992.7345834391593),c(119.05954985109253,378.2768151181308,185.48159219801417,128.7407961232339),c(986.2834314825072,745.8979453033566,328.0626800781203,302.11173490252224),c(523.2740709504807,694.3954681276485,336.89513684945433,597.9294753279087),c(1562.4728579223624,763.6574201915316,422.0652557158894,220.28980669975581),c(30.8672907021351,179.37069637056908,238.47633282601822,184.81456510135357),c(339.5401977234861,447.5387671820139,310.3977665354523,205.98527379717427))
+targetgene="ABT1"
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+
+## code
+
+targetmatvec=unlist(targetmat)+1
+yrange=range(targetmatvec[targetmatvec>0]);
+# yrange[1]=1; # set the minimum value to 1
+for(i in 1:length(targetmat)){
+ vali=targetmat[[i]]+1;
+ if(i==1){
+ plot(1:length(vali),vali,type='b',las=1,pch=20,main=paste('sgRNAs in',targetgene),ylab='Read counts',xlab='Samples',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt='n',log='y')
+ axis(1,at=1:length(vali),labels=(collabel),las=2)
+ # lines(0:100,rep(1,101),col='black');
+ }else{
+ lines(1:length(vali),vali,type='b',pch=20,col=colors[(i %% length(colors))])
+ }
+}
+
+
+
+par(mfrow=c(1,1));
+@
+%
+
+
+<>=
+par(mfrow=c(2,2));
+
+# parameters
+# Do not modify the variables beginning with "__"
+targetmat=list(c(492.4067802483456,221.99343610218943,309.7668767660713,102.99263689858714),c(243.9985836454489,239.7529109903646,130.59418226186713,174.51530141149487),c(734.9354929079785,673.0840982618383,620.7955330709046,470.9052231529845),c(1074.4756906314647,950.1319065173708,1100.902647569846,743.8357109342404),c(702.5983312200275,1010.5141211371663,1291.4313579229083,1017.3383800315995),c(1647.7253750996879,760.1055252138966,685.7771793171477,608.2287390177673),c(951.0065278229242,864.8864270541301,606.9159581445226,769.0116888427839),c(435.0818118015233,435.1071347602913,275.69882921949727,339.8757017653375),c(89.66213013477338,209.56180368046682,208.8245136651112,304.4004601669353),c(1328.7633711776252,1571.7135276035012,1122.983789498181,1356.6419004808338))
+targetgene="ADIRF"
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+
+## code
+
+targetmatvec=unlist(targetmat)+1
+yrange=range(targetmatvec[targetmatvec>0]);
+# yrange[1]=1; # set the minimum value to 1
+for(i in 1:length(targetmat)){
+ vali=targetmat[[i]]+1;
+ if(i==1){
+ plot(1:length(vali),vali,type='b',las=1,pch=20,main=paste('sgRNAs in',targetgene),ylab='Read counts',xlab='Samples',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt='n',log='y')
+ axis(1,at=1:length(vali),labels=(collabel),las=2)
+ # lines(0:100,rep(1,101),col='black');
+ }else{
+ lines(1:length(vali),vali,type='b',pch=20,col=colors[(i %% length(colors))])
+ }
+}
+
+
+
+# parameters
+# Do not modify the variables beginning with "__"
+targetmat=list(c(216.0710349149457,289.479440677255,192.42137966120518,498.36992632594104),c(1127.391046120839,1198.764554951823,371.5940741654094,370.2013115188104),c(1111.2224652768637,1038.9292809582466,948.227323379644,922.3562815584581),c(1164.137820766238,1204.0923974182756,1686.9992433247955,2089.033985093009),c(48.505742531926586,248.63264843445216,665.5887066969557,248.8988725049189),c(501.2260061632414,387.1565525622184,436.5757204116524,314.69972385679404),c(1975.5066049366465,1797.2588586833258,1628.3264947723626,1289.6966864967521),c(213.13129294331378,376.5008676293133,404.4003421732214,482.921030791153),c(2012.2533795820452,1989.0611874756173,1064.3110409457481,431.9968936579627),c(264.57677744687226,353.4135502746856,442.25372833608145,191.6807408945927))
+targetgene="ABCF1"
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+
+## code
+
+targetmatvec=unlist(targetmat)+1
+yrange=range(targetmatvec[targetmatvec>0]);
+# yrange[1]=1; # set the minimum value to 1
+for(i in 1:length(targetmat)){
+ vali=targetmat[[i]]+1;
+ if(i==1){
+ plot(1:length(vali),vali,type='b',las=1,pch=20,main=paste('sgRNAs in',targetgene),ylab='Read counts',xlab='Samples',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt='n',log='y')
+ axis(1,at=1:length(vali),labels=(collabel),las=2)
+ # lines(0:100,rep(1,101),col='black');
+ }else{
+ lines(1:length(vali),vali,type='b',pch=20,col=colors[(i %% length(colors))])
+ }
+}
+
+
+
+par(mfrow=c(1,1));
+@
+
+\newpage\section{Comparison results of HL60 final,KBM7 final vs HL60 initial,KBM7 initial pos.}
+
+The following figure shows the distribution of RRA score in the comparison HL60 final,KBM7 final vs HL60 initial,KBM7 initial pos., and the RRA scores of 10 genes.
+
+<>=
+gstable=read.table('output.gene_summary.txt',header=T)
+@
+%
+
+
+<>=#
+#
+# parameters
+# Do not modify the variables beginning with "__"
+
+# gstablename='__GENE_SUMMARY_FILE__'
+startindex=9
+# outputfile='__OUTPUT_FILE__'
+targetgenelist=c("ACRC","AGAP3","ADCK4","AHRR","ADRBK1","ADK","ADCK1","ADARB2","ACSS2","ADNP")
+# samplelabel=sub('.\w+.\w+$','',colnames(gstable)[startindex]);
+samplelabel='HL60_final,KBM7_final_vs_HL60_initial,KBM7_initial pos.'
+
+
+# You need to write some codes in front of this code:
+# gstable=read.table(gstablename,header=T)
+# pdf(file=outputfile,width=6,height=6)
+
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+######
+# function definition
+
+plotrankedvalues<-function(val, tglist, ...){
+
+ plot(val,log='y',ylim=c(max(val),min(val)),type='l',lwd=2, ...)
+ if(length(tglist)>0){
+ for(i in 1:length(tglist)){
+ targetgene=tglist[i];
+ tx=which(names(val)==targetgene);ty=val[targetgene];
+ points(tx,ty,col=colors[(i %% length(colors)) ],cex=2,pch=20)
+ # text(tx+50,ty,targetgene,col=colors[i])
+ }
+ legend('topright',tglist,pch=20,pt.cex = 2,cex=1,col=colors)
+ }
+}
+
+
+
+plotrandvalues<-function(val,targetgenelist, ...){
+ # choose the one with the best distance distribution
+
+ mindiffvalue=0;
+ randval=val;
+ for(i in 1:20){
+ randval0=sample(val)
+ vindex=sort(which(names(randval0) %in% targetgenelist))
+ if(max(vindex)>0.9*length(val)){
+ # print('pass...')
+ next;
+ }
+ mindiffind=min(diff(vindex));
+ if (mindiffind > mindiffvalue){
+ mindiffvalue=mindiffind;
+ randval=randval0;
+ # print(paste('Diff: ',mindiffvalue))
+ }
+ }
+ plot(randval,log='y',ylim=c(max(randval),min(randval)),pch=20,col='grey', ...)
+
+ if(length(targetgenelist)>0){
+ for(i in 1:length(targetgenelist)){
+ targetgene=targetgenelist[i];
+ tx=which(names(randval)==targetgene);ty=randval[targetgene];
+ points(tx,ty,col=colors[(i %% length(colors)) ],cex=2,pch=20)
+ text(tx+50,ty,targetgene,col=colors[i])
+ }
+ }
+
+}
+
+
+
+
+# set.seed(1235)
+
+
+
+pvec=gstable[,startindex]
+names(pvec)=gstable[,'id']
+pvec=sort(pvec);
+
+plotrankedvalues(pvec,targetgenelist,xlab='Genes',ylab='RRA score',main=paste('Distribution of RRA scores in \n',samplelabel))
+
+# plotrandvalues(pvec,targetgenelist,xlab='Genes',ylab='RRA score',main=paste('Distribution of RRA scores in \n',samplelabel))
+
+
+pvec=gstable[,startindex+1]
+names(pvec)=gstable[,'id']
+pvec=sort(pvec);
+
+plotrankedvalues(pvec,targetgenelist,xlab='Genes',ylab='p value',main=paste('Distribution of p values in \n',samplelabel))
+
+# plotrandvalues(pvec,targetgenelist,xlab='Genes',ylab='p value',main=paste('Distribution of p values in \n',samplelabel))
+
+
+
+# you need to write after this code:
+# dev.off()
+
+
+
+
+@
+%%
+\clearpage
+\newpage
+The following figures show the distribution of sgRNA read counts (normalized) of selected genes in selected samples.
+%
+
+
+<>=
+par(mfrow=c(2,2));
+
+# parameters
+# Do not modify the variables beginning with "__"
+targetmat=list(c(461.5394895462105,502.5931393353569,445.40817718298644,889.1697652244688),c(76.43329126242978,90.5733219296933,447.30084649112945,357.0411412484354),c(258.6972935036084,685.515730683561,533.7327448963265,560.7376897811967),c(232.23961575892122,681.9638357059259,275.69882921949727,467.47213525636494),c(1393.4376945535273,1472.2604682297203,1039.706339939889,532.7008052921368),c(2395.88970688001,2441.927797124084,2462.9936596634266,2461.5240218762324),c(495.34652221997754,605.5980936867728,1159.575396122279,1617.5565806239213),c(682.0201374186041,822.2636873225097,1572.1773052974536,1333.7546478367033),c(961.2956247236359,1097.5355480892247,959.5833392285019,905.1908420753603),c(1940.2297012770634,1289.3378768815162,942.5493154552149,1103.737758763192))
+targetgene="ACRC"
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+
+## code
+
+targetmatvec=unlist(targetmat)+1
+yrange=range(targetmatvec[targetmatvec>0]);
+# yrange[1]=1; # set the minimum value to 1
+for(i in 1:length(targetmat)){
+ vali=targetmat[[i]]+1;
+ if(i==1){
+ plot(1:length(vali),vali,type='b',las=1,pch=20,main=paste('sgRNAs in',targetgene),ylab='Read counts',xlab='Samples',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt='n',log='y')
+ axis(1,at=1:length(vali),labels=(collabel),las=2)
+ # lines(0:100,rep(1,101),col='black');
+ }else{
+ lines(1:length(vali),vali,type='b',pch=20,col=colors[(i %% length(colors))])
+ }
+}
+
+
+
+# parameters
+# Do not modify the variables beginning with "__"
+targetmat=list(c(1387.5582106102636,1120.6228654438523,1214.4628060584262,1111.1761158725344),c(388.0459402554127,509.69692929062694,933.0859689144999,750.1297054113762),c(326.3113588511425,635.7892009966705,960.8451187672639,615.6670961271097),c(1328.7633711776252,1038.9292809582466,1346.3187678590552,1596.3858719281006),c(352.7690365958297,234.42506852391205,310.3977665354523,429.1359870774464),c(693.7791053051318,678.4119407282909,784.1959833405838,895.4637597016048),c(837.8264619150956,719.2587329710938,374.74852301231437,993.8789460713658),c(365.99787546817333,369.3970776740432,333.74068800254935,746.6966175147567),c(707.0079441774753,635.7892009966705,837.1907239685878,1465.3563505404536),c(486.5272963050818,673.0840982618383,784.8268731099647,734.6808098765882))
+targetgene="AGAP3"
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+
+## code
+
+targetmatvec=unlist(targetmat)+1
+yrange=range(targetmatvec[targetmatvec>0]);
+# yrange[1]=1; # set the minimum value to 1
+for(i in 1:length(targetmat)){
+ vali=targetmat[[i]]+1;
+ if(i==1){
+ plot(1:length(vali),vali,type='b',las=1,pch=20,main=paste('sgRNAs in',targetgene),ylab='Read counts',xlab='Samples',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt='n',log='y')
+ axis(1,at=1:length(vali),labels=(collabel),las=2)
+ # lines(0:100,rep(1,101),col='black');
+ }else{
+ lines(1:length(vali),vali,type='b',pch=20,col=colors[(i %% length(colors))])
+ }
+}
+
+
+
+# parameters
+# Do not modify the variables beginning with "__"
+targetmat=list(c(830.4771069860158,864.8864270541301,1349.4732167059603,740.974804353724),c(1481.6299537024847,1994.38902994207,2044.082852794442,1810.9538654668238),c(1234.6916280854039,1299.9935618144214,1357.6747837079133,2232.6514954349277),c(224.89026082984142,188.25043381465665,700.2876440129107,81.24974688666317),c(812.8386551562243,845.3510046771374,946.334654071501,999.6007592323984),c(1978.4463469082782,1751.0842239740703,2659.2003779409174,2851.1794981425537),c(565.9003295391435,776.0890526132542,878.1985589783528,445.72924524444096),c(680.5502664327881,534.5601941340722,550.7667686696135,1025.9210997731484),c(161.68580843975528,333.87812789769293,275.0679394501163,465.18340999195186),c(2523.768482645998,2445.4796921017187,2153.226782897355,1516.8526689897471))
+targetgene="ADCK4"
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+
+## code
+
+targetmatvec=unlist(targetmat)+1
+yrange=range(targetmatvec[targetmatvec>0]);
+# yrange[1]=1; # set the minimum value to 1
+for(i in 1:length(targetmat)){
+ vali=targetmat[[i]]+1;
+ if(i==1){
+ plot(1:length(vali),vali,type='b',las=1,pch=20,main=paste('sgRNAs in',targetgene),ylab='Read counts',xlab='Samples',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt='n',log='y')
+ axis(1,at=1:length(vali),labels=(collabel),las=2)
+ # lines(0:100,rep(1,101),col='black');
+ }else{
+ lines(1:length(vali),vali,type='b',pch=20,col=colors[(i %% length(colors))])
+ }
+}
+
+
+
+# parameters
+# Do not modify the variables beginning with "__"
+targetmat=list(c(345.4196816667499,163.38716897121142,474.42910657451245,481.2044868428432),c(415.9734889859159,372.9489726516783,212.6098522813972,349.03060282298975),c(1.469870985815957,83.46953197442323,0.0,62.9399447713588),c(351.29916561001374,150.9555365494888,288.9475143764983,416.54799812317464),c(561.4907165816957,170.49095892648148,199.3611671243962,411.97054759434855),c(251.34793857452865,221.99343610218943,1564.6066280648815,1502.5481360871656),c(736.4053638937945,893.3015868752103,1114.782222496228,459.46159683091923),c(338.07032673767014,607.3740411755903,378.5338616286004,65.22867003577186),c(1230.2820151279561,525.6804566899846,837.1907239685878,945.2435342025885))
+targetgene="AHRR"
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+
+## code
+
+targetmatvec=unlist(targetmat)+1
+yrange=range(targetmatvec[targetmatvec>0]);
+# yrange[1]=1; # set the minimum value to 1
+for(i in 1:length(targetmat)){
+ vali=targetmat[[i]]+1;
+ if(i==1){
+ plot(1:length(vali),vali,type='b',las=1,pch=20,main=paste('sgRNAs in',targetgene),ylab='Read counts',xlab='Samples',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt='n',log='y')
+ axis(1,at=1:length(vali),labels=(collabel),las=2)
+ # lines(0:100,rep(1,101),col='black');
+ }else{
+ lines(1:length(vali),vali,type='b',pch=20,col=colors[(i %% length(colors))])
+ }
+}
+
+
+
+par(mfrow=c(1,1));
+@
+%
+
+
+<>=
+par(mfrow=c(2,2));
+
+# parameters
+# Do not modify the variables beginning with "__"
+targetmat=list(c(371.87735941143717,877.3180594758527,2395.4884543396593,1564.9158995424211),c(1109.7525942910477,1138.3823403320275,970.308465307979,999.0285779162951),c(1462.5216308868773,1209.420239884728,1537.4783679814984,1519.14139425416),c(586.4785233405669,987.4268037825386,743.8190381001997,1312.0117578247794),c(1018.6205931704583,717.4827854822763,1070.619938639558,1144.3626322065236),c(1269.9685317449869,1212.9721348623632,1591.1039983788835,1624.9949377332637),c(1321.4140162485455,1795.4829111945082,1478.8056194290655,1237.056005415252),c(908.3802692342615,832.9193722554148,1639.6825106212207,1268.5259778009315),c(923.078979092421,758.3295777250792,1479.4365091984464,1275.964334910274),c(680.5502664327881,634.013253507853,318.5993335374053,631.1159916618979))
+targetgene="ADRBK1"
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+
+## code
+
+targetmatvec=unlist(targetmat)+1
+yrange=range(targetmatvec[targetmatvec>0]);
+# yrange[1]=1; # set the minimum value to 1
+for(i in 1:length(targetmat)){
+ vali=targetmat[[i]]+1;
+ if(i==1){
+ plot(1:length(vali),vali,type='b',las=1,pch=20,main=paste('sgRNAs in',targetgene),ylab='Read counts',xlab='Samples',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt='n',log='y')
+ axis(1,at=1:length(vali),labels=(collabel),las=2)
+ # lines(0:100,rep(1,101),col='black');
+ }else{
+ lines(1:length(vali),vali,type='b',pch=20,col=colors[(i %% length(colors))])
+ }
+}
+
+
+
+# parameters
+# Do not modify the variables beginning with "__"
+targetmat=list(c(1472.810727787589,1829.225913482041,1263.0413183007631,1315.444845721399),c(208.7216799858659,65.71005708624807,292.1019632234033,350.17496545519623),c(1011.2712382413785,1166.7975001531076,652.9709113093356,860.5606994193058),c(557.0811036242477,685.515730683561,875.0441101314478,1019.6271052960126),c(363.0581334965414,825.8155823001447,736.8792506370087,349.602784139093),c(1505.14788947554,451.09066215964896,653.6018010787167,991.0180394908496),c(198.43258308515422,28.41515982108025,249.83234867487624,114.43626322065236),c(438.02155377315523,74.58979453033565,254.87946682992424,231.16125170571777),c(804.0194292413286,472.4020320254591,1336.2245315489592,1203.2973077651598),c(454.19013461713075,490.1615069136343,896.4943622904019,685.4732166917076))
+targetgene="ADK"
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+
+## code
+
+targetmatvec=unlist(targetmat)+1
+yrange=range(targetmatvec[targetmatvec>0]);
+# yrange[1]=1; # set the minimum value to 1
+for(i in 1:length(targetmat)){
+ vali=targetmat[[i]]+1;
+ if(i==1){
+ plot(1:length(vali),vali,type='b',las=1,pch=20,main=paste('sgRNAs in',targetgene),ylab='Read counts',xlab='Samples',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt='n',log='y')
+ axis(1,at=1:length(vali),labels=(collabel),las=2)
+ # lines(0:100,rep(1,101),col='black');
+ }else{
+ lines(1:length(vali),vali,type='b',pch=20,col=colors[(i %% length(colors))])
+ }
+}
+
+
+
+# parameters
+# Do not modify the variables beginning with "__"
+targetmat=list(c(662.9118146029966,1008.7381736483488,1101.533537339227,1694.8010582978616),c(1547.7741480642028,1965.9738701209897,1869.9572764452857,2353.9539344488194),c(1459.5818889152454,1179.2291325748304,1296.4784760779562,1222.1792911965672),c(1193.5352404825571,1355.0479339677643,1622.0175970785526,1905.9359639399652),c(868.6937526172306,701.4992580829187,720.4761166331027,603.6512884889412),c(798.1399452980647,768.9852626579842,1478.8056194290655,1756.0244591209105),c(1168.5474337236858,907.5091667857504,879.4603385171149,977.8578692204745),c(809.8989131845924,687.2916781723785,678.8373918539567,865.7103312642352),c(1246.4505959719315,753.0017352586266,1301.5255942330043,1264.5207085882087),c(826.0674940285679,797.4004224790644,977.8791425405509,2066.7189137649816))
+targetgene="ADCK1"
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+
+## code
+
+targetmatvec=unlist(targetmat)+1
+yrange=range(targetmatvec[targetmatvec>0]);
+# yrange[1]=1; # set the minimum value to 1
+for(i in 1:length(targetmat)){
+ vali=targetmat[[i]]+1;
+ if(i==1){
+ plot(1:length(vali),vali,type='b',las=1,pch=20,main=paste('sgRNAs in',targetgene),ylab='Read counts',xlab='Samples',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt='n',log='y')
+ axis(1,at=1:length(vali),labels=(collabel),las=2)
+ # lines(0:100,rep(1,101),col='black');
+ }else{
+ lines(1:length(vali),vali,type='b',pch=20,col=colors[(i %% length(colors))])
+ }
+}
+
+
+
+# parameters
+# Do not modify the variables beginning with "__"
+targetmat=list(c(1863.7964100146337,1585.9211075140413,1761.4442361117538,1464.211987908247),c(742.2848478370584,598.4943037315028,943.8110949939769,820.5080072920774),c(1568.3523418656262,2083.1864043829455,1810.6536381234716,1887.6261618246608),c(1018.6205931704583,513.248824268262,679.4682816233377,824.5132765048003),c(1140.6198849931827,1191.6607649965529,880.0912282864958,977.8578692204745),c(135.22813069506805,118.98848175077354,351.40560154521734,399.95473995618005),c(665.8515565746286,701.4992580829187,986.7115993118849,746.6966175147567),c(418.9132309575478,300.1351256101601,376.6411923204574,645.4205245644794),c(561.4907165816957,543.4399315781598,881.9838975946388,580.7640358448108),c(442.4311667306031,229.0972260574595,395.5678854018874,651.142337725512))
+targetgene="ADARB2"
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+
+## code
+
+targetmatvec=unlist(targetmat)+1
+yrange=range(targetmatvec[targetmatvec>0]);
+# yrange[1]=1; # set the minimum value to 1
+for(i in 1:length(targetmat)){
+ vali=targetmat[[i]]+1;
+ if(i==1){
+ plot(1:length(vali),vali,type='b',las=1,pch=20,main=paste('sgRNAs in',targetgene),ylab='Read counts',xlab='Samples',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt='n',log='y')
+ axis(1,at=1:length(vali),labels=(collabel),las=2)
+ # lines(0:100,rep(1,101),col='black');
+ }else{
+ lines(1:length(vali),vali,type='b',pch=20,col=colors[(i %% length(colors))])
+ }
+}
+
+
+
+par(mfrow=c(1,1));
+@
+%
+
+
+<>=
+par(mfrow=c(2,2));
+
+# parameters
+# Do not modify the variables beginning with "__"
+targetmat=list(c(734.9354929079785,358.74139274113816,541.9343118982795,378.7840312603593),c(595.2977492554626,591.3905137762326,1061.787481868224,887.4532212761591),c(1655.0747300287676,943.0281165621008,1069.358159100796,2038.1098479598186),c(626.1650399575977,884.4218494311227,517.3296108924205,858.2719741548927),c(680.5502664327881,747.673892792174,533.1018551269456,1016.194017399393),c(662.9118146029966,777.8650001020718,864.9498738213518,787.3214909580882),c(880.4527205037583,621.5816210861304,671.8976043907657,1040.7978139918332),c(94.07174309222125,447.5387671820139,711.6436598617687,927.5059134033875),c(399.80490814194036,806.280159923152,1147.58849050404,1059.1076161071376),c(698.1887182625796,531.0082991564371,504.0809257354195,347.8862401907832))
+targetgene="ACSS2"
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+
+## code
+
+targetmatvec=unlist(targetmat)+1
+yrange=range(targetmatvec[targetmatvec>0]);
+# yrange[1]=1; # set the minimum value to 1
+for(i in 1:length(targetmat)){
+ vali=targetmat[[i]]+1;
+ if(i==1){
+ plot(1:length(vali),vali,type='b',las=1,pch=20,main=paste('sgRNAs in',targetgene),ylab='Read counts',xlab='Samples',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt='n',log='y')
+ axis(1,at=1:length(vali),labels=(collabel),las=2)
+ # lines(0:100,rep(1,101),col='black');
+ }else{
+ lines(1:length(vali),vali,type='b',pch=20,col=colors[(i %% length(colors))])
+ }
+}
+
+
+
+# parameters
+# Do not modify the variables beginning with "__"
+targetmat=list(c(408.62413405683606,523.9045092011671,483.89245311522745,701.494293542599),c(1805.0015705819953,1434.9655709645526,1712.2348341000356,2152.546111180471),c(3017.64513388016,2642.609863360463,1834.6274493599499,3573.2723190648703),c(1649.1952460855039,783.1928425685244,773.4708572611067,1332.0381038883936),c(959.82575373782,1397.6706736993847,1429.5962174173474,2811.126806015325),c(495.34652221997754,301.9110730989776,336.89513684945433,555.015876620164),c(1491.9190506031964,1331.9606166131366,2087.614246881731,1983.1804416139055),c(429.2023278582595,889.7496918975753,567.8007924429005,1132.9190058844583),c(427.7324568724435,573.6310388880576,655.4944703868597,899.4690289143276),c(690.8393633334998,767.2093151691668,1040.33722970927,993.3067647552625))
+targetgene="ADNP"
+collabel=c("HL60_initial","KBM7_initial","HL60_final","KBM7_final")
+
+# set up color using RColorBrewer
+#library(RColorBrewer)
+#colors <- brewer.pal(length(targetgenelist), "Set1")
+
+colors=c( "#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#A65628", "#F781BF",
+ "#999999", "#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3",
+ "#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
+ "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F")
+
+
+## code
+
+targetmatvec=unlist(targetmat)+1
+yrange=range(targetmatvec[targetmatvec>0]);
+# yrange[1]=1; # set the minimum value to 1
+for(i in 1:length(targetmat)){
+ vali=targetmat[[i]]+1;
+ if(i==1){
+ plot(1:length(vali),vali,type='b',las=1,pch=20,main=paste('sgRNAs in',targetgene),ylab='Read counts',xlab='Samples',xlim=c(0.7,length(vali)+0.3),ylim = yrange,col=colors[(i %% length(colors))],xaxt='n',log='y')
+ axis(1,at=1:length(vali),labels=(collabel),las=2)
+ # lines(0:100,rep(1,101),col='black');
+ }else{
+ lines(1:length(vali),vali,type='b',pch=20,col=colors[(i %% length(colors))])
+ }
+}
+
+
+
+par(mfrow=c(1,1));
+@
+%__INDIVIDUAL_PAGE__
+
+
+
+
+
+
+
+
+
+\end{document}
+
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diff -r 93f268840b0c -r 9cd937788131 test-data/test2.fastq.gz
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