changeset 0:bf0ebc9921f2 draft default tip

planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/wisecondorx commit b391b0f3348bd86a5c276dc4d3ff9dc98890c115
author artbio
date Sun, 15 Dec 2024 16:37:13 +0000
parents
children
files macro.xml test-data/0.ref.npz test-data/1.ref.npz test-data/2.ref.npz test-data/3.ref.npz test-data/4.ref.npz test-data/5.ref.npz test-data/6.ref.npz test-data/7.ref.npz test-data/8.ref.npz test-data/9.ref.npz test-data/chr1.png test-data/chr10.png test-data/chr11.png test-data/chr12.png test-data/chr13.png test-data/chr14.png test-data/chr15.png test-data/chr16.png test-data/chr17.png test-data/chr18.png test-data/chr19.png test-data/chr2.png test-data/chr20.png test-data/chr21.png test-data/chr22.png test-data/chr3.png test-data/chr4.png test-data/chr5.png test-data/chr6.png test-data/chr7.png test-data/chr8.png test-data/chr9.png test-data/chrX.png test-data/genome_wide.png test-data/input_reference_predict.10000kb.npz test-data/input_sample_predict.npz test-data/npz_convert_input.bam test-data/npz_convert_output.npz test-data/output_reference.npz test-data/predict_abberations.bed test-data/predict_bins.bed test-data/predict_segments.bed test-data/predict_statistics.txt wisecondor_npz_converter.xml wisecondor_predict.xml wisecondor_reference_builder.xml
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/macro.xml	Sun Dec 15 16:37:13 2024 +0000
@@ -0,0 +1,54 @@
+<macros>
+    <token name="@VERSION@">1.2.9</token>
+    <token name="@WRAPPER_VERSION@">@VERSION@+galaxy0</token>
+    <token name="@PROFILE@">23.0</token>
+    <token name="@pipefail@"><![CDATA[set -o | grep -q pipefail && set -o pipefail;]]></token>
+
+    <xml name="requirements">
+        <requirements>
+            <requirement type="package" version="@VERSION@">wisecondorx</requirement>
+        </requirements>
+    </xml>
+<token name="@help@"><![CDATA[
+**What it does**
+
+WisecondorX, which uses a within-sample normalization technique, detects Copy
+Number Variation from BAM input files.
+
+It is important that **no** read quality filtering is executed prior to running
+WisecondorX: this software requires low-quality reads to distinguish informative
+bins from non-informative ones.
+
+There are three main stages (converting, reference build and predicting) when
+using WisecondorX:
+
+**1. Convert .bam files** of aligned reads to .npz files (for both normal and
+tumor samples) using the Galaxy tool **WisecondorX convert bam to npz**
+
+**2. Buid a reference index** from .npz files from **normal** samples using the
+Galaxy tool **WisecondorX build reference**.
+
+.. class:: warningmark
+
+Automated gender prediction, required to consistently analyze sex chromosomes,
+is based on a Gaussian mixture model. If few samples (<20) are included during
+reference creation, or not both male and female samples (for NIPT, this means
+male and female feti) are represented, this process might not be accurate.
+Therefore, alternatively, one can manually tweak the --yfrac parameter.
+
+.. class:: warningmark
+
+It is of paramount importance that the reference set consists of exclusively
+negative (normal) control samples that originate from the same sequencer, mapper,
+reference genome, type of material, ... etc, as the test samples. As a rule of
+thumb, think of all laboratory and in silico steps: the more sources of bias that
+can be omitted, the better.
+
+Try to include at least 50 samples per reference. The more the better, yet, from
+500 on it is unlikely to observe additional improvement concerning normalization.
+
+**3. Predict Copy Number Variantions** from the reference index and tumor .npz cases
+of interest using the Galaxy tool **WisecondorX predict CNVs**
+
+]]></token>
+</macros>
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/predict_abberations.bed	Sun Dec 15 16:37:13 2024 +0000
@@ -0,0 +1,1 @@
+chr	start	end	ratio	zscore	type
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/predict_bins.bed	Sun Dec 15 16:37:13 2024 +0000
@@ -0,0 +1,317 @@
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+1	110000001	120000000	1:110000001-120000000	-0.056066962637539804	-2.2951856527187857
+1	120000001	130000000	1:120000001-130000000	nan	nan
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+1	140000001	150000000	1:140000001-150000000	nan	nan
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+8	80000001	90000000	8:80000001-90000000	0.020977868179333847	0.8465568956728705
+8	90000001	100000000	8:90000001-100000000	0.019529059695413593	0.7891355936784927
+8	100000001	110000000	8:100000001-110000000	-0.009372010272758387	-0.37286404501355586
+8	110000001	120000000	8:110000001-120000000	-0.04350484795453549	-1.7197203517706365
+8	120000001	130000000	8:120000001-130000000	-0.01001300559828008	-0.3982858046251174
+8	130000001	140000000	8:130000001-140000000	-0.027278377664516667	-1.0863311105342262
+8	140000001	150000000	8:140000001-150000000	-0.0434510360509685	-1.7208233888905153
+9	1	10000000	9:1-10000000	0.00939095744597003	0.37154175158765707
+9	10000001	20000000	9:10000001-20000000	0.0019249124835837665	0.07342608914972887
+9	20000001	30000000	9:20000001-30000000	nan	nan
+9	30000001	40000000	9:30000001-40000000	-0.006796307090005416	-0.2727496852182093
+9	40000001	50000000	9:40000001-50000000	nan	nan
+9	50000001	60000000	9:50000001-60000000	nan	nan
+9	60000001	70000000	9:60000001-70000000	nan	nan
+9	70000001	80000000	9:70000001-80000000	0.0025526559473861327	0.0981313556088763
+9	80000001	90000000	9:80000001-90000000	-0.02448900495179313	-0.968970897673129
+9	90000001	100000000	9:90000001-100000000	0.024891848129699464	0.9954336107390866
+9	100000001	110000000	9:100000001-110000000	0.018809839649419256	0.7498408267228337
+9	110000001	120000000	9:110000001-120000000	-0.04960957964146416	-1.942777261947177
+9	120000001	130000000	9:120000001-130000000	-0.00880375959644314	-0.35207401910845065
+9	130000001	140000000	9:130000001-140000000	-0.00961278379143818	-0.3842451478426133
+10	1	10000000	10:1-10000000	-0.025282396561535605	-1.0051701514792954
+10	10000001	20000000	10:10000001-20000000	0.014700629086388927	0.5970088802031047
+10	20000001	30000000	10:20000001-30000000	0.03226806397356753	1.3151250942193684
+10	30000001	40000000	10:30000001-40000000	-0.044954214404446385	-1.777300103274846
+10	40000001	50000000	10:40000001-50000000	-0.08566090692175034	-3.4192839149753174
+10	50000001	60000000	10:50000001-60000000	-0.0002981917221372385	-0.009226194426872652
+10	60000001	70000000	10:60000001-70000000	0.005933641740981277	0.24189224310483795
+10	70000001	80000000	10:70000001-80000000	-0.02021300199741985	-0.80448151484732
+10	80000001	90000000	10:80000001-90000000	-0.032276367309482405	-1.2808944140132101
+10	90000001	100000000	10:90000001-100000000	-0.03001445466447732	-1.1907196189948817
+10	100000001	110000000	10:100000001-110000000	0.030702786791715383	1.250784726710977
+10	110000001	120000000	10:110000001-120000000	0.041646696009583324	1.7020972757726456
+10	120000001	130000000	10:120000001-130000000	0.023523487829799603	0.9565739621521425
+10	130000001	140000000	10:130000001-140000000	0.016196438602470276	0.66113114292475
+11	1	10000000	11:1-10000000	-0.03581463295432329	-1.401227458445462
+11	10000001	20000000	11:10000001-20000000	-0.017426172731554397	-0.6840871824118568
+11	20000001	30000000	11:20000001-30000000	-0.016057168068517712	-0.6310352631494758
+11	30000001	40000000	11:30000001-40000000	0.028593228960990178	1.1524815930111891
+11	40000001	50000000	11:40000001-50000000	0.024046428670010934	0.9683294352339441
+11	50000001	60000000	11:50000001-60000000	0.07314593248780782	3.0785594770749514
+11	60000001	70000000	11:60000001-70000000	-0.02231004227988148	-0.8764230177364339
+11	70000001	80000000	11:70000001-80000000	-0.011843445202051618	-0.4612881506573179
+11	80000001	90000000	11:80000001-90000000	0.02013371494259112	0.8103226720367603
+11	90000001	100000000	11:90000001-100000000	-0.013531497054077872	-0.531615896319081
+11	100000001	110000000	11:100000001-110000000	-0.02063422614779682	-0.8107615887621088
+11	110000001	120000000	11:110000001-120000000	0.016014952692370556	0.6509540447682887
+11	120000001	130000000	11:120000001-130000000	-0.009585136504013464	-0.3759242928080648
+11	130000001	140000000	11:130000001-140000000	-0.029685439779832762	-1.1626572875695504
+12	1	10000000	12:1-10000000	0.04585161432403065	1.8983401150846326
+12	10000001	20000000	12:10000001-20000000	-0.023303772572693334	-0.9188252776378798
+12	20000001	30000000	12:20000001-30000000	0.020644315173378985	0.8495055595070082
+12	30000001	40000000	12:30000001-40000000	-0.049162667885723314	-1.9344085270918951
+12	40000001	50000000	12:40000001-50000000	-0.0082981643232976	-0.32109393356467186
+12	50000001	60000000	12:50000001-60000000	0.000859952443344143	0.04677607044841259
+12	60000001	70000000	12:60000001-70000000	0.026913795813337957	1.1061885853025268
+12	70000001	80000000	12:70000001-80000000	-0.018566870097600816	-0.730090634783613
+12	80000001	90000000	12:80000001-90000000	-0.029162570168812678	-1.1502818710671616
+12	90000001	100000000	12:90000001-100000000	-0.007273742063167581	-0.28006008566146756
+12	100000001	110000000	12:100000001-110000000	-0.07954015039252423	-3.1064146584347982
+12	110000001	120000000	12:110000001-120000000	-0.00039144919853810727	-0.0020859199471905693
+12	120000001	130000000	12:120000001-130000000	0.049086335033781195	2.026816643189698
+12	130000001	140000000	12:130000001-140000000	-0.021744777628390038	-0.8631011291002287
+13	1	10000000	13:1-10000000	nan	nan
+13	10000001	20000000	13:10000001-20000000	nan	nan
+13	20000001	30000000	13:20000001-30000000	-0.009656753617364098	-0.36729210552032326
+13	30000001	40000000	13:30000001-40000000	0.042061924743976936	1.7302316151921193
+13	40000001	50000000	13:40000001-50000000	0.055373175144399024	2.2816529396093266
+13	50000001	60000000	13:50000001-60000000	-0.01667652168496713	-0.6457846781153704
+13	60000001	70000000	13:60000001-70000000	0.008346377008774032	0.3520582734267505
+13	70000001	80000000	13:70000001-80000000	-0.002554264101621818	-0.08477369667991035
+13	80000001	90000000	13:80000001-90000000	-0.00534912014120097	-0.1962231214032517
+13	90000001	100000000	13:90000001-100000000	-0.008908840705848515	-0.3376075679247741
+13	100000001	110000000	13:100000001-110000000	0.02150370071364117	0.8837193830095974
+13	110000001	120000000	13:110000001-120000000	0.007256660392835141	0.3126957510931542
+14	1	10000000	14:1-10000000	nan	nan
+14	10000001	20000000	14:10000001-20000000	nan	nan
+14	20000001	30000000	14:20000001-30000000	-0.006626145326900847	-0.2561565594381251
+14	30000001	40000000	14:30000001-40000000	-0.015509173662509394	-0.6143267630669463
+14	40000001	50000000	14:40000001-50000000	0.02149949964626884	0.8800890548705425
+14	50000001	60000000	14:50000001-60000000	0.03679880936188848	1.5091649420610784
+14	60000001	70000000	14:60000001-70000000	0.053773215331583905	2.214968649614744
+14	70000001	80000000	14:70000001-80000000	0.021317126214166163	0.8785517000899401
+14	80000001	90000000	14:80000001-90000000	-0.03151336720618568	-1.2500552624481234
+14	90000001	100000000	14:90000001-100000000	-0.0416870692710144	-1.650184415935656
+14	100000001	110000000	14:100000001-110000000	0.0035058727944338825	0.1490161232441591
+15	1	10000000	15:1-10000000	nan	nan
+15	10000001	20000000	15:10000001-20000000	nan	nan
+15	20000001	30000000	15:20000001-30000000	nan	nan
+15	30000001	40000000	15:30000001-40000000	0.007651171848000582	0.31475373097690357
+15	40000001	50000000	15:40000001-50000000	0.05016403399546734	2.0638124180547837
+15	50000001	60000000	15:50000001-60000000	-0.033641545470941475	-1.3331935846842662
+15	60000001	70000000	15:60000001-70000000	0.0032394081307219507	0.1364261219479641
+15	70000001	80000000	15:70000001-80000000	-0.013406817539286676	-0.5319858771048407
+15	80000001	90000000	15:80000001-90000000	-0.02241717655226552	-0.8907392725849449
+15	90000001	100000000	15:90000001-100000000	-0.023091155667494666	-0.9174842369620465
+15	100000001	110000000	15:100000001-110000000	0.04875490806051794	2.011437626389599
+16	1	10000000	16:1-10000000	0.015613534890434941	0.6237512966184409
+16	10000001	20000000	16:10000001-20000000	0.0005439011028519588	0.01255598433935668
+16	20000001	30000000	16:20000001-30000000	0.0732324156428063	3.0177334336393016
+16	30000001	40000000	16:30000001-40000000	-0.054469928590655185	-2.162403810073181
+16	40000001	50000000	16:40000001-50000000	0.01813709854863917	0.7218951831778254
+16	50000001	60000000	16:50000001-60000000	-0.05723333688043617	-2.2724986805052834
+16	60000001	70000000	16:60000001-70000000	-0.004184381546241695	-0.17790195574423653
+16	70000001	80000000	16:70000001-80000000	0.007301717962691849	0.28234174549518515
+16	80000001	90000000	16:80000001-90000000	0.00937900180269912	0.37011615304819756
+16	90000001	100000000	16:90000001-100000000	nan	nan
+17	1	10000000	17:1-10000000	0.0004316751575414166	0.025851364090371753
+17	10000001	20000000	17:10000001-20000000	0.005501661360702138	0.22983479607633225
+17	20000001	30000000	17:20000001-30000000	0.0376323612752476	1.5790453167930645
+17	30000001	40000000	17:30000001-40000000	-0.007997853490625685	-0.3117155882221979
+17	40000001	50000000	17:40000001-50000000	0.06843368075845338	2.8199217972801147
+17	50000001	60000000	17:50000001-60000000	-0.01785908067289162	-0.7026255025479773
+17	60000001	70000000	17:60000001-70000000	0.058455624981440794	2.401753572591004
+17	70000001	80000000	17:70000001-80000000	0.026984064071546392	1.1021456817476445
+17	80000001	90000000	17:80000001-90000000	0.006869817773389827	0.28502645834951745
+18	1	10000000	18:1-10000000	-0.0212176294191172	-0.8282615354884798
+18	10000001	20000000	18:10000001-20000000	0.0849653258080829	3.4829633648718272
+18	20000001	30000000	18:20000001-30000000	0.009665993221586318	0.3934968783370261
+18	30000001	40000000	18:30000001-40000000	0.022234215861628295	0.8982327858168634
+18	40000001	50000000	18:40000001-50000000	-0.014751098567981444	-0.5746053905214142
+18	50000001	60000000	18:50000001-60000000	0.012358147464810629	0.5012432038919561
+18	60000001	70000000	18:60000001-70000000	-0.008122874604008016	-0.31342402755897286
+18	70000001	80000000	18:70000001-80000000	-0.0033932308036662196	-0.12633373312774904
+18	80000001	90000000	18:80000001-90000000	0.10634975850569614	4.3918802853640795
+19	1	10000000	19:1-10000000	nan	nan
+19	10000001	20000000	19:10000001-20000000	0.02338718480906324	0.9371000508939006
+19	20000001	30000000	19:20000001-30000000	0.0016192329112033454	0.06455322910870305
+19	30000001	40000000	19:30000001-40000000	-0.016414448306286206	-0.6495603510470805
+19	40000001	50000000	19:40000001-50000000	0.013953162403958663	0.5592941216205073
+19	50000001	60000000	19:50000001-60000000	-0.026491449724493948	-1.0463463060421774
+20	1	10000000	20:1-10000000	0.004415934577788096	0.18094749263990748
+20	10000001	20000000	20:10000001-20000000	-0.0015257958192696254	-0.05635617426161793
+20	20000001	30000000	20:20000001-30000000	0.011356150557422921	0.463349549613987
+20	30000001	40000000	20:30000001-40000000	0.04832339461875347	1.9651712862465622
+20	40000001	50000000	20:40000001-50000000	0.002058925822068644	0.08669518357715515
+20	50000001	60000000	20:50000001-60000000	-0.026454965118318553	-1.0414052703283316
+20	60000001	70000000	20:60000001-70000000	-0.01404748466152417	-0.5512510786934586
+21	1	10000000	21:1-10000000	nan	nan
+21	10000001	20000000	21:10000001-20000000	-0.025683332190871457	-1.0094328127541692
+21	20000001	30000000	21:20000001-30000000	0.02657805642164083	1.0778969720886815
+21	30000001	40000000	21:30000001-40000000	-0.015665486408755112	-0.6115881238744478
+21	40000001	50000000	21:40000001-50000000	-0.0063924278396725815	-0.24736849021826626
+22	1	10000000	22:1-10000000	nan	nan
+22	10000001	20000000	22:10000001-20000000	-0.035979913832053415	-1.4319862380618358
+22	20000001	30000000	22:20000001-30000000	-0.03775440025299403	-1.5030086324021878
+22	30000001	40000000	22:30000001-40000000	-0.0327155577009055	-1.3044020825473626
+22	40000001	50000000	22:40000001-50000000	-0.02443136403628654	-0.976368192179424
+22	50000001	60000000	22:50000001-60000000	0.042313429133239586	1.7364268589651852
+X	1	10000000	X:1-10000000	0.04931851358472728	1.6704531245154441
+X	10000001	20000000	X:10000001-20000000	0.02718845309018554	0.9440176239356763
+X	20000001	30000000	X:20000001-30000000	-0.014267351268826181	-0.3871718107217453
+X	30000001	40000000	X:30000001-40000000	0.025980354460086477	0.9046807483268727
+X	40000001	50000000	X:40000001-50000000	-0.009742885062837143	-0.2437390422675029
+X	50000001	60000000	X:50000001-60000000	-0.014551565643648038	-0.39616685107614386
+X	60000001	70000000	X:60000001-70000000	-0.08497689046044601	-2.5713018064280253
+X	70000001	80000000	X:70000001-80000000	-0.015594033231660176	-0.42914452052792057
+X	80000001	90000000	X:80000001-90000000	-0.030528785180684786	-0.8989872729642105
+X	90000001	100000000	X:90000001-100000000	-0.024914008099105458	-0.722918403493542
+X	100000001	110000000	X:100000001-110000000	-0.019859615807420662	-0.5638350192329954
+X	110000001	120000000	X:110000001-120000000	0.0075845539896018865	0.30974726841857264
+X	120000001	130000000	X:120000001-130000000	-0.05913853363578263	-1.7855707521141684
+X	130000001	140000000	X:130000001-140000000	-0.02374419086758032	-0.6861487961271984
+X	140000001	150000000	X:140000001-150000000	-0.005291502639923923	-0.10218348201809535
+X	150000001	160000000	X:150000001-160000000	-0.021520485843592178	-0.6161712091875068
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/predict_segments.bed	Sun Dec 15 16:37:13 2024 +0000
@@ -0,0 +1,28 @@
+chr	start	end	ratio	zscore
+1	1	120000000	-0.0087	-2.538405323843277
+1	140000001	250000000	0.0176	4.312862224344486
+2	1	250000000	0.0077	3.3452597487045215
+3	1	200000000	0.0058	2.311500455599722
+4	1	40000000	0.0007	0.11656739335236131
+4	40000001	190000000	0.0006	0.35088837729023276
+5	1	190000000	-0.0138	-4.742762233161156
+6	1	170000000	0.0029	0.9290111777306987
+7	1	160000000	-0.0066	-1.3173166420256102
+8	1	150000000	-0.0093	-2.345755449706625
+9	1	20000000	0.0057	0.5378706474020528
+9	20000001	40000000	-0.0068	-0.5822999425114906
+9	60000001	140000000	-0.0066	-0.8909887079018787
+10	1	140000000	-0.0053	-0.972447941393507
+11	1	140000000	-0.0011	-0.25869752816517777
+12	1	140000000	-0.0067	-1.6120716034316234
+13	20000001	120000000	0.0091	2.6165198496794595
+14	20000001	110000000	0.0046	1.4493631003182375
+15	30000001	110000000	0.0022	0.5631104559578264
+16	1	90000000	0.0009	0.20349127260764568
+17	1	90000000	0.0198	3.2916417620408067
+18	1	90000000	0.0209	2.8871676559099937
+19	10000001	60000000	-0.0008	-0.09701491554952066
+20	1	70000000	0.0034	0.49591449488386785
+21	10000001	50000000	-0.0053	-0.6285903890420564
+22	10000001	60000000	-0.0177	-1.875889555547745
+X	1	160000000	-0.0134	-2.6093805092022024
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/predict_statistics.txt	Sun Dec 15 16:37:13 2024 +0000
@@ -0,0 +1,29 @@
+chr	ratio.mean	ratio.median	zscore
+1	0.003256724685060297	0.009032538940713365	1.1604576995182534
+2	0.007728111371764734	0.00879518825265517	3.6168182974192224
+3	0.0057970691646083835	0.007918358867360545	2.2102487208570447
+4	0.0005794303608920617	-0.0038693714215764057	0.3050780556626696
+5	-0.013750074657332427	-0.00306199917667051	-5.00766851062217
+6	0.00293681601872286	-0.0016253998352964258	0.9407744372804929
+7	-0.0066155513952186815	-0.007596035725320216	-1.3291500169147508
+8	-0.009253570570903735	-0.01001300559828008	-2.3586673175031008
+9	-0.004174118616434959	-0.0024356973032108246	-0.7243064497148664
+10	-0.005266146751525984	0.0028177250094220192	-1.0963168057162755
+11	-0.0010682214397647377	-0.012687471128064745	-0.25403103304752794
+12	-0.006720586939014568	-0.007785953193232591	-1.7313975674091997
+13	0.009139617144346813	0.002351198145606662	2.7174009747784944
+14	0.004617644740226149	0.0035058727944338825	1.4966978929197126
+15	0.0021565565774295426	-0.005083704704282363	0.5800013406347537
+16	0.0009244703405124733	0.007301717962691849	0.20870556732386122
+17	0.01982791519920036	0.006869817773389827	3.1146698354398854
+18	0.020898589066626748	0.009665993221586318	2.845910113450034
+19	-0.000657740980105667	0.0016192329112033454	-0.08006761423301532
+20	0.003446546608787667	0.002058925822068644	0.5033887759993748
+21	-0.005290652555760193	-0.011028957124213846	-0.5341417465937656
+22	-0.017713587100928845	-0.0327155577009055	-1.6790692284983704
+X	-0.013378674115274611	-0.015072799437654107	-2.6107602961602137
+Gender based on --yfrac (or manually overridden by --gender): F
+Number of reads: 2081160
+Standard deviation of the ratios per chromosome: 0.00932
+Median segment variance per bin (doi: 10.1093/nar/gky1263): 0.0008
+Copy number profile abnormality (CPA) score (doi: 10.1186/s13073-020-00735-4): 2.32398
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/wisecondor_npz_converter.xml	Sun Dec 15 16:37:13 2024 +0000
@@ -0,0 +1,57 @@
+<tool id="wisecondorx_npz_converter" name="WisecondorX convert" version="@WRAPPER_VERSION@" profile="@PROFILE@">
+    <description>
+        bam to npz
+    </description>
+    <macros>
+        <import>macro.xml</import>
+    </macros>
+    <expand macro="requirements"/>
+    <stdio>
+        <exit_code range="1:" level="fatal" description="Error occured" />
+    </stdio>
+    <command detect_errors="exit_code"><![CDATA[
+    @pipefail@
+    ln -f -s $bam.metadata.bam_index input.bam.bai &&
+    ln -f -s $bam input.bam &&
+    printf "Creating 5kb bins for file $bam.element_identifier" &&
+    WisecondorX convert input.bam output.npz
+    ]]></command>
+    <inputs>
+        <param name="bam" type="data" label="Bam input" format="bam"
+               help="input Bam is converted in .npz file"/>
+     </inputs>
+    <outputs>
+        <data name="npz" format="npz" from_work_dir="output.npz" label="${on_string}.npz" />
+    </outputs>
+    <tests>
+        <test expect_num_outputs="1">
+            <param ftype="bam" name="bam" value="npz_convert_input.bam" />
+            <output name="npz" ftype="npz" file="npz_convert_output.npz" compare="sim_size" delta="10000"/>
+        </test>
+    </tests>
+    <help>
+@help@
+<![CDATA[
+.. class:: infomark
+
+**WisecondorX convert input.bam/cram output.npz [--optional arguments]**
+
+Option List::
+
+  --reference   Fasta reference to be used with cram inputs.
+                This option is currently not available in this Galaxy wrapper,
+                which takes only bam inputs.
+  --binsize     Size per bin in bp; the reference bin size should be a multiple of this value.
+                Note that this parameter does not impact the resolution, yet it
+                can be used to optimize processing speed (default: x=5e3).
+                The --binsize parameter is currently not exposed in this Galaxy
+                wrapper and is fixed to 5e3
+  --normdup     Use this flag to avoid duplicate removal.
+                The --normdup parameter is currently not exposed in this Galaxy
+                wrapper. Default is to remove duplicates.
+
+    ]]></help>
+    <citations>
+        <citation type="doi">10.1093/nar/gky1263</citation>
+    </citations>
+</tool>
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/wisecondor_predict.xml	Sun Dec 15 16:37:13 2024 +0000
@@ -0,0 +1,112 @@
+<tool id="wisecondorx_predict" name="WisecondorX predict" version="@WRAPPER_VERSION@" profile="@PROFILE@">
+    <description>
+        CNVs
+    </description>
+    <macros>
+        <import>macro.xml</import>
+    </macros>
+    <expand macro="requirements"/>
+    <stdio>
+        <exit_code range="1:" level="fatal" description="Error occured" />
+    </stdio>
+    <command detect_errors="exit_code"><![CDATA[
+    @pipefail@
+    ln -s $npz_input sample.npz &&
+    ln -s $reference reference.npz &&
+    WisecondorX predict sample.npz reference.npz sample --plot --bed
+    ]]></command>
+    <inputs>
+        <param name="npz_input" type="data" format="npz" label="npz file from sample to analyse"/>
+        <param name="reference" type="data" format="npz" label="npz reference built with WisecondorX build"/>
+    </inputs>
+    <outputs>
+        <data name="aberrations" format="bed" label="sample abberations" from_work_dir="sample_aberrations.bed"/>
+        <data name="bins" format="bed" label="sample bins" from_work_dir="sample_bins.bed"/>
+        <data name="segments" format="bed" label="sample segments" from_work_dir="sample_segments.bed"/>
+        <data name="statistics" format="txt" label="statistics" from_work_dir="sample_statistics.txt"/>
+        <collection name="plots" type="list" format="png" label="CNV plots">
+            <discover_datasets pattern="__name_and_ext__" directory="sample.plots" />
+        </collection>
+    </outputs>
+    <tests>
+        <test expect_num_outputs="5">
+            <param name="npz_input" value="input_sample_predict.npz" ftype="npz" />
+            <param name="reference" value="input_reference_predict.10000kb.npz" />
+            <output name="aberrations" ftype="bed" file="predict_abberations.bed" />
+            <output name="bins" ftype="bed" file="predict_bins.bed" compare="sim_size" delta="1000"/>
+            <output name="segments" ftype="bed" file="predict_segments.bed"/>
+            <output name="statistics" ftype="txt" file="predict_statistics.txt" compare="sim_size" delta="1000"/>
+            <output_collection name="plots" type="list">
+                <element name="chr1" file="chr1.png" compare="sim_size" delta="10000"/>
+                <element name="chr10" file="chr10.png" compare="sim_size" delta="10000"/>
+                <element name="chr11" file="chr11.png" compare="sim_size" delta="10000"/>
+                <element name="chr12" file="chr12.png" compare="sim_size" delta="10000"/>
+                <element name="chr13" file="chr13.png" compare="sim_size" delta="10000"/>
+                <element name="chr14" file="chr14.png" compare="sim_size" delta="10000"/>
+                <element name="chr15" file="chr15.png" compare="sim_size" delta="10000"/>
+                <element name="chr16" file="chr16.png" compare="sim_size" delta="10000"/>
+                <element name="chr17" file="chr17.png" compare="sim_size" delta="10000"/>
+                <element name="chr18" file="chr18.png" compare="sim_size" delta="10000"/>
+                <element name="chr19" file="chr19.png" compare="sim_size" delta="10000"/>
+                <element name="chr2" file="chr2.png" compare="sim_size" delta="10000"/>
+                <element name="chr20" file="chr20.png" compare="sim_size" delta="10000"/>
+                <element name="chr21" file="chr21.png" compare="sim_size" delta="10000"/>
+                <element name="chr22" file="chr22.png" compare="sim_size" delta="10000"/>
+                <element name="chr3" file="chr3.png" compare="sim_size" delta="10000"/>
+                <element name="chr4" file="chr4.png" compare="sim_size" delta="10000"/>
+                <element name="chr5" file="chr5.png" compare="sim_size" delta="10000"/>
+                <element name="chr6" file="chr6.png" compare="sim_size" delta="10000"/>
+                <element name="chr7" file="chr7.png" compare="sim_size" delta="10000"/>
+                <element name="chr8" file="chr8.png" compare="sim_size" delta="10000"/>
+                <element name="chr9" file="chr9.png" compare="sim_size" delta="10000"/>
+                <element name="chrX" file="chrX.png" compare="sim_size" delta="10000"/>
+                <element name="genome_wide" file="genome_wide.png" compare="sim_size" delta="10000"/>
+            </output_collection>
+        </test>
+    </tests>
+    <help>
+@help@
+<![CDATA[
+.. class:: infomark
+
+**WisecondorX predict test_input.npz reference_input.npz output_id [--optional arguments]**
+
+Option List::
+
+  --minrefbins      Minimum amount of sensible reference bins per target bin;
+                    should generally not be tweaked (default: x=150)
+  --maskrepeats     Bins with distances > mean + sd * 3 in the reference will be
+                    masked. This parameter represents the number of masking cycles
+                    and defines the stringency of the blacklist (default: x=5)
+                    **Should be a multiple of the 5e3**.
+                    Not exposed in this Galaxy wrapper.
+  --zscore          Z-score cutoff to call segments as aberrations (default: x=5)
+  --alpha           P-value cutoff for calling circular binary segmentation
+                    breakpoints (default: x=1e-4).
+                    Not exposed in this Galaxy wrapper.
+  --beta            When beta is given, --zscore is ignored. Beta sets a ratio
+                    cutoff for aberration calling. It's a number between 0 (liberal)
+                    and 1 (conservative) and, when used, is optimally close to the
+                    purity (e.g. fetal/tumor fraction)
+                    Not exposed in this Galaxy wrapper.
+  --blacklist       Blacklist for masking additional regions; requires headerless
+                    .bed file. This is particularly useful when the reference set
+                    is too small to recognize some obvious loci (such as centromeres).
+                    Not exposed in this Galaxy wrapper.
+  --gender          Force WisecondorX to analyze this case as male (M) or female (F).
+                    Useful when e.g. dealing with a loss of chromosome Y, which
+                    causes erroneous gender predictions (choices: x=F or x=M).
+                    Not exposed in this Galaxy wrapper.
+  --bed             Outputs tab-delimited .bed files.
+  --plot            Outputs custom .png plots, directly interpretable.
+  --ylim  [a,b]     Force WisecondorX to use y-axis interval [a,b] during plotting, e.g. [-2,2].
+                    Not exposed in this Galaxy wrapper.
+  --cairo           Some operating systems require the cairo bitmap type to write plots.
+                    Not exposed in this Galaxy wrapper.
+  --seed            Random seed for segmentation algorithm (default:None).
+                    Not exposed in this Galaxy wrapper.
+    ]]></help>
+    <citations>
+        <citation type="doi">10.1093/nar/gky1263</citation>
+    </citations>
+</tool>
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/wisecondor_reference_builder.xml	Sun Dec 15 16:37:13 2024 +0000
@@ -0,0 +1,66 @@
+<tool id="wisecondorx_reference_builder" name="WisecondorX build" version="@WRAPPER_VERSION@" profile="@PROFILE@">
+    <description>
+        reference
+    </description>
+    <macros>
+        <import>macro.xml</import>
+    </macros>
+    <expand macro="requirements"/>
+    <stdio>
+        <exit_code range="1:" level="fatal" description="Error occured" />
+    </stdio>
+    <command detect_errors="exit_code"><![CDATA[
+    @pipefail@
+    #for $num, $file in enumerate($npz_inputs):
+        ln -s $file "${num}.npz" &&
+    #end for
+    WisecondorX newref *.npz reference.npz
+        --binsize ${bin}
+        --cpus \${GALAXY_SLOTS:-4} &&
+    mv reference.npz $npz
+    ]]></command>
+    <inputs>
+        <param name="npz_inputs" type="data" label="npz inputs" multiple="True" format="npz"
+               help="Build reference from npz inputs from normal sample (at least 10 samples required)"/>
+        <param name="bin" size="9" type="integer" value="100000" label="Bin size in nucleotides"
+               help="Bin default value is 100 kb (100000)" />
+     </inputs>
+    <outputs>
+        <data name="npz" format="npz" label="reference_${bin}nt" />
+    </outputs>
+    <tests>
+        <test expect_num_outputs="1">
+            <param name="npz_inputs"
+                   value="0.ref.npz,1.ref.npz,2.ref.npz,3.ref.npz,4.ref.npz,5.ref.npz,6.ref.npz,7.ref.npz,8.ref.npz,9.ref.npz"/>
+            <param name="bin" value="10000" />
+            <output name="npz" ftype="npz" file="output_reference.npz" compare="sim_size" delta="10000"/>
+        </test>
+    </tests>
+    <help>
+@help@
+<![CDATA[
+.. class:: infomark
+
+**WisecondorX newref reference_input_dir/*.npz reference_output.npz [--optional arguments]**
+
+Option List::
+
+  --nipt        Always include this flag for the generation of a NIPT reference
+  --binsize     Size per bin in bp, defines the resolution of the output (default: x=1e5)
+                **Should be a multiple of the 5e3**
+  --refsize     Amount of reference locations per target;
+                should generally not be tweaked (default: x=300)
+  --yfrac       Y read fraction cutoff, in order to manually define gender.
+                Setting this to 1 will treat all samples as female.
+                This parameter is not currently exposed in the Galaxy wrapper.
+  --plotyfrac   plots Y read fraction histogram and Gaussian mixture fit to file x,
+                can help when setting --yfrac manually; software quits after plotting
+                The --normdup parameter is currently not exposed in this Galaxy
+                wrapper. Default is to remove duplicates.
+  --cpus        Number of threads requested (This is defined by the Galaxy administrator)
+
+    ]]></help>
+    <citations>
+        <citation type="doi">10.1093/nar/gky1263</citation>
+    </citations>
+</tool>