Mercurial > repos > iuc > tooldistillator_summarize
changeset 5:07d093aaf3b4 draft default tip
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/tooldistillator commit 164bcc563f8495d4bb1ce14b574aef9287904f40
| author | iuc |
|---|---|
| date | Thu, 10 Apr 2025 15:02:36 +0000 (3 days ago) |
| parents | 24eec94e6dfc |
| children | |
| files | macro.xml test-data/checkm2/DIAMOND_RESULTS.tsv test-data/checkm2/checkm2.log test-data/checkm2/quality_report.tsv |
| diffstat | 4 files changed, 163 insertions(+), 2 deletions(-) [+] |
line wrap: on
line diff
--- a/macro.xml Thu Oct 17 08:00:41 2024 +0000 +++ b/macro.xml Thu Apr 10 15:02:36 2025 +0000 @@ -1,7 +1,7 @@ <?xml version="1.0"?> <macros> - <token name="@TOOL_VERSION@">0.9.1</token> - <token name="@VERSION_SUFFIX@">1</token> + <token name="@TOOL_VERSION@">0.9.2</token> + <token name="@VERSION_SUFFIX@">0</token> <token name="@PROFILE@">21.05</token> <xml name="version_command"> <version_command><![CDATA[tooldistillator --version]]></version_command>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/checkm2/DIAMOND_RESULTS.tsv Thu Apr 10 15:02:36 2025 +0000 @@ -0,0 +1,100 @@ +bin_semibin_SASB_CSM7KOLE.1ΩCSM7KOLE_k117_49428_2 UniRef100_A0A0N7IEW1~K00616 91.7 218 18 0 1 218 1 218 3.7e-113 412.5 +bin_semibin_SASB_CSM7KOLE.1ΩCSM7KOLE_k117_49428_3 UniRef100_B5R745~K05776 39.4 358 206 4 14 367 49 399 3.5e-63 247.3 +bin_semibin_SASB_CSM7KOLE.1ΩCSM7KOLE_k117_28292_2 UniRef100_E6STV5~K03402 94.3 157 9 0 1 157 1 157 3.4e-76 289.3 +bin_semibin_SASB_CSM7KOLE.1ΩCSM7KOLE_k117_28292_4 UniRef100_A0A1A9I3U8~K05970 45.9 427 197 7 12 409 12 433 1.2e-101 375.2 +bin_semibin_SASB_CSM7KOLE.1ΩCSM7KOLE_k117_14200_2 UniRef100_E6SQC7~K01200 86.9 665 87 0 1 665 1 665 0.0e+00 1218.0 +bin_semibin_SASB_CSM7KOLE.1ΩCSM7KOLE_k117_63629_1 UniRef100_E6SR16~K03711 95.1 162 7 1 1 161 1 162 6.6e-83 311.6 +bin_semibin_SASB_CSM7KOLE.1ΩCSM7KOLE_k117_114_1 UniRef100_A0A139LU84~K01952 94.2 1011 59 0 1 1011 38 1048 0.0e+00 1941.8 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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/checkm2/checkm2.log Thu Apr 10 15:02:36 2025 +0000 @@ -0,0 +1,11 @@ +[03/03/2025 11:20:03 AM] INFO: Running CheckM2 version 1.0.2 +[03/03/2025 11:20:03 AM] INFO: Custom database path provided for predict run. Checking database at Database/CheckM2_database/uniref100.KO.1.dmnd... +[03/03/2025 11:20:10 AM] INFO: Running quality prediction workflow with 5 threads. +[03/03/2025 11:20:12 AM] INFO: Calling genes in 50 bins with 5 threads: +[03/03/2025 11:20:59 AM] WARNING: Skipping protein file batches/batch_0/checkm2/protein_files/bin_concoct_SASB_HSMA33OT.11.faa as it was empty. +[03/03/2025 11:20:59 AM] INFO: Calculating metadata for 49 bins with 5 threads: +[03/03/2025 11:20:59 AM] INFO: Annotating input genomes with DIAMOND using 5 threads +[03/03/2025 11:23:40 AM] INFO: Processing DIAMOND output +[03/03/2025 11:23:40 AM] INFO: Predicting completeness and contamination using ML models. +[03/03/2025 11:23:44 AM] INFO: Parsing all results and constructing final output table. +[03/03/2025 11:23:44 AM] INFO: CheckM2 finished successfully.
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/checkm2/quality_report.tsv Thu Apr 10 15:02:36 2025 +0000 @@ -0,0 +1,50 @@ +Name Completeness Contamination Completeness_Model_Used Translation_Table_Used Coding_Density Contig_N50 Average_Gene_Length Genome_Size GC_Content Total_Coding_Sequences Total_Contigs Max_Contig_Length Additional_Notes +bin_concoct_SASB_CSM7KOLE.0 22.51 0.0 Neural Network (Specific Model) 11 0.887 2144 267.22576530612247 708085 0.53 784 324 5294 None +bin_concoct_SASB_CSM7KOLE.1 15.91 5.09 Neural Network (Specific Model) 11 0.845 4814 222.07713884992987 1119464 0.47 1426 273 50470 None +bin_concoct_SASB_CSM7KOLE.20 6.38 0.0 Gradient Boost (General Model) 11 0.974 3001 300.0 16618 0.61 18 6 4049 None +bin_concoct_SASB_CSM7KOLE.22 100.0 2.05 Neural Network (Specific Model) 11 0.87 22717 300.98043641835966 2755022 0.54 2658 187 146684 None +bin_concoct_SASB_CSM7KOLE.24 6.38 0.0 Gradient Boost (General Model) 11 0.926 5194 268.5 5194 0.45 6 1 5194 None +bin_concoct_SASB_CSM7KOLE.3 6.38 0.0 Gradient Boost (General Model) 11 0.818 4650 264.75 7724 0.36 8 3 4650 None +bin_concoct_SASB_CSM7KOLE.30 6.38 0.0 Gradient Boost (General Model) 11 0.796 1887 501.0 1887 0.5 1 1 1887 None +bin_concoct_SASB_HSMA33MG.1 33.58 0.68 Neural Network (Specific Model) 11 0.856 2959 250.53061224489795 987394 0.59 1127 345 13858 None +bin_concoct_SASB_HSMA33MG.10 6.38 0.0 Gradient Boost (General Model) 11 0.998 2318 386.0 2318 0.36 2 1 2318 None +bin_concoct_SASB_HSMA33MG.12 9.66 0.29 Neural Network (Specific Model) 11 0.887 1956 238.57806691449815 432765 0.41 538 204 12095 None +bin_concoct_SASB_HSMA33MG.13 6.65 0.0 Gradient Boost (General Model) 11 0.936 1726 269.5 1726 0.45 2 1 1726 None +bin_concoct_SASB_HSMA33MG.8 6.38 0.0 Gradient Boost (General Model) 11 0.794 1759 233.0 1759 0.53 2 1 1759 None +bin_concoct_SASB_HSMA33MG.9 53.69 21.09 Neural Network (Specific Model) 11 0.901 2957 269.85174585002864 3130308 0.44 3494 1086 18806 None +bin_concoct_SASB_HSMA33OT.0 4.43 0.0 Neural Network (Specific Model) 11 0.851 1985 214.93157894736842 143344 0.38 190 71 3816 None +bin_concoct_SASB_HSMA33OT.10 6.38 0.0 Gradient Boost (General Model) 11 0.966 11244 210.76666666666668 19477 0.36 30 4 11244 None +bin_concoct_SASB_HSMA33OT.14 6.38 0.0 Gradient Boost (General Model) 11 0.509 1707 290.0 1707 0.44 1 1 1707 None +bin_concoct_SASB_HSMA33OT.16 9.03 0.06 Neural Network (Specific Model) 11 0.881 1824 231.57877813504822 244747 0.42 311 130 3723 None +bin_concoct_SASB_HSMA33OT.18 6.38 0.0 Gradient Boost (General Model) 11 0.958 1602 256.0 1602 0.36 2 1 1602 None +bin_concoct_SASB_HSMA33OT.2 6.38 0.0 Gradient Boost (General Model) 11 0.941 1704 345.0 3299 0.35 3 2 1704 None +bin_concoct_SASB_HSMA33OT.3 5.64 0.0 Gradient Boost (General Model) 11 0.839 2532 203.5 4366 0.44 6 2 2532 None +bin_concoct_SASB_HSMA33OT.4 6.38 0.0 Gradient Boost (General Model) 11 0.634 2866 202.0 2866 0.42 3 1 2866 None +bin_concoct_SASB_HSMA33OT.6 6.42 0.0 Gradient Boost (General Model) 11 0.915 1816 233.42857142857142 10707 0.61 14 6 2097 None +bin_concoct_SASB_MSM5LLDE.16 6.38 0.0 Gradient Boost (General Model) 11 0.998 1592 530.0 1592 0.6 1 1 1592 None +bin_concoct_SASB_MSM5LLDE.19 6.38 0.0 Gradient Boost (General Model) 11 0.819 1941 68.75 1941 0.39 8 1 1941 None +bin_concoct_SASB_MSM5LLDE.2 6.38 0.0 Gradient Boost (General Model) 11 0.876 1618 236.5 1618 0.54 2 1 1618 None +bin_concoct_SASB_MSM5LLDE.20 49.54 0.72 Neural Network (Specific Model) 11 0.901 2559 261.2743158588856 2632930 0.42 3033 1029 33333 None +bin_concoct_SASB_MSM5LLDE.21 99.55 8.64 Neural Network (Specific Model) 11 0.9 81127 346.90618336886996 4332951 0.46 3752 143 235469 None +bin_concoct_SASB_MSM5LLDE.27 9.51 0.07 Neural Network (Specific Model) 11 0.877 1958 217.07469879518072 307709 0.57 415 150 5816 None +bin_concoct_SASB_MSM5LLDE.28 6.38 0.0 Gradient Boost (General Model) 11 0.952 1638 260.0 1638 0.59 2 1 1638 None +bin_concoct_SASB_MSM5LLDE.6 5.91 0.0 Gradient Boost (General Model) 11 0.91 1987 228.10714285714286 20991 0.61 28 11 2365 None +bin_concoct_SASB_MSM5LLDE.7 5.03 0.0 Gradient Boost (General Model) 11 0.999 1689 282.0 1689 0.65 2 1 1689 None +bin_metabat_SASB_CSM7KOLE.10 45.04 8.76 Neural Network (Specific Model) 11 0.903 2382 261.277639046538 3814277 0.41 4405 1544 17510 None +bin_metabat_SASB_CSM7KOLE.2 18.36 0.04 Neural Network (Specific Model) 11 0.924 2177 272.32474226804123 514039 0.49 582 230 4454 None +bin_metabat_SASB_CSM7KOLE.3 15.42 0.06 Neural Network (Specific Model) 11 0.944 2547 288.0351906158358 623088 0.49 682 253 7390 None +bin_metabat_SASB_CSM7KOLE.7 5.83 0.18 Neural Network (Specific Model) 11 0.906 146684 275.6360153256705 237533 0.52 261 10 146684 None +bin_metabat_SASB_MSM5LLDE.1 85.75 0.14 Neural Network (Specific Model) 11 0.897 81302 343.6424261670372 3612719 0.46 3149 65 235469 None +bin_metabat_SASB_MSM5LLDE.2 96.34 0.33 Neural Network (Specific Model) 11 0.866 76315 307.9110091743119 2321808 0.57 2180 40 221393 None +bin_semibin_SASB_CSM7KOLE.0 17.68 0.13 Neural Network (Specific Model) 11 0.895 3290 276.360396039604 467082 0.59 505 137 14331 None +bin_semibin_SASB_CSM7KOLE.1 45.77 0.88 Gradient Boost (General Model) 11 0.901 4330 318.24455825864277 1653306 0.5 1562 386 16396 None +bin_semibin_SASB_CSM7KOLE.10 10.46 0.46 Neural Network (Specific Model) 11 0.884 8223 264.5268817204301 749398 0.39 837 118 30972 None +bin_semibin_SASB_CSM7KOLE.11 14.55 3.97 Neural Network (Specific Model) 11 0.89 19781 259.4004424778761 788274 0.5 904 74 146684 None +bin_semibin_SASB_CSM7KOLE.14 92.78 0.09 Neural Network (Specific Model) 11 0.897 65685 352.9744467860906 4474676 0.42 3796 113 353143 None +bin_semibin_SASB_CSM7KOLE.16 10.61 0.0 Neural Network (Specific Model) 11 0.881 3151 281.17182130584195 278023 0.52 291 84 5610 None +bin_semibin_SASB_CSM7KOLE.3 10.48 1.74 Neural Network (Specific Model) 11 0.919 3218 322.7874125874126 752315 0.41 715 228 6603 None +bin_semibin_SASB_HSMA33MG.1 37.55 7.85 Neural Network (Specific Model) 11 0.909 3945 314.83505866114564 1502934 0.43 1449 378 18770 None +bin_semibin_SASB_HSMA33MG.2 9.86 0.19 Neural Network (Specific Model) 11 0.84 5391 209.15863141524105 478276 0.48 643 94 18806 None +bin_semibin_SASB_MSM5LLDE.0 6.09 0.04 Neural Network (Specific Model) 11 0.889 3492 214.14640198511165 290530 0.54 403 76 32205 None +bin_semibin_SASB_MSM5LLDE.1 29.89 0.02 Neural Network (Specific Model) 11 0.914 3803 319.14351851851853 1129847 0.42 1080 302 10395 None +bin_semibin_SASB_MSM5LLDE.10 6.39 0.04 Neural Network (Specific Model) 11 0.838 6460 243.23076923076923 214350 0.48 247 38 17791 None