Package: clearCNV
ClearCNV: Clinical sequencing panel CNV caller and visualizerCode Formatting:blackInstallationcondaClearCNV is available on conda:https://anaconda.org/bioconda/clearcnvI'd recommend to create a conda env:mamba create -n clearcnv clearcnv -c conda-forge -c biocondaorconda create -n clearcnv clearcnv -c conda-forge -c biocondaThen clone this repo to your favorite locationgit clone git@github.com:bihealth/clear-cnv.gitandcd clear-cnvinto it. Now you can run the commands listed below.Quick run checks and examplesSample reassignment:Create all filesExecute the shell commamd (from within the cloned repo directory):clearCNV workflow_reassignment --workdir tests/testdata/ --reference tests/testdata/test_reassignment_ref.fa --metafile tests/testdata/test_reassign_meta.tsv --coverages tests/testdata/test_reassignment_coverages.tsv --bedfile tests/testdata/test_reassignment_union.bed --cores 2INPUT: working directory given by--workdir, the files given by--referenceand--metafile.OUTPUT: files created at--coveragesand--bedfile. They are used in the next step.If you want to create the necessary files for yourown data just edit the meta.tsv file analogously to the example atclearCNV/tests/testdata/meta.tsv, where you can add more rows for each targets file (BED-file). It is recommended to use absolute paths in the meta file.Optionally,drmaacan be used, if the two flags are present:--drmaa_mem 1600 --drmaa_time 4:00,
where drmaa is given 16 Gb memory per core and and four hours maximum running time.
Also, a cluster config file in .json format can be given with--cluster_configfile config.jsonVisualize sample reassignment:Visualize and adjust the clusterings and final panel assignmentsExecute the shell commamd (from within the cloned repo directory):clearCNV visualize_reassignment --metafile tests/testdata/meta.tsv --coverages tests/testdata/cov_reassignment.tsv --bedfile tests/testdata/reassignment_union.bed --new_panel_assignments_directory tests/testdata/panel_assignmentsINPUT: files given by--metafile,--coveragesand--bedfile.OUTPUT: files found in given directory--new_panel_assignments_directory.CNV callingMatch scoresAt first, match scores are claculated. Go to the directoryclear-cnv/and execute the shell command:clearCNV matchscores -p testpanel -c tests/testdata/cov.tsv -m tests/testdata/matchscores.tsvThis creates a match score matrix which is used in the CNV calling step.CNV callsNow execute this shell command:clearCNV cnv_calling -p testpanel -c tests/testdata/cov.tsv -a tests/testdata/testpanel/analysis -m tests/testdata/matchscores.tsv -C tests/testdata/testpanel/results/cnv_calls.tsv -r tests/testdata/testpanel/results/rscores.tsv -z tests/testdata/testpanel/results/zscores.tsv -g 15 -u 3This creates the filetests/testdata/testpanel/results/cnv_calls.tsvwhich shows one called deletion. if you copy & paste this for your own data, please don't use the-g 15 -u 3configuration. We use these in here just to be able to work with a tiny example.More files for analysis can now be found intests/testdata/testpanel/analysis.HOW TO and WORKFLOWclearCNV comprises of two major workflows and three major commads:workflowre-assignmenta)clearCNV workflow_reassignmentb)clearCNV visualize_reassignmentCNV callinga)clearCNV workflow_cnv_callingpreparationsSome files have to be acquired or created before these commands can be run:re-assignment:a) For each sequencing panel a .bed file is needed following thisform. Such a file should always exist in the case of targeted sequencing.b) For each sequencing panel (or .bed-file containing all target informations) a simple list of the according .bam files is needed. An example can be foundhere. Make sure to use absolute paths for this file on custim data.c) meta-file. This file is a tab-separated file and one example can be foundhere. To avoid any confusion, we recommend using absolute paths here again.CNV calling:a) A reference file. It must be the same that was used to create the alignment files (.bam files).b)workflow_cnv_callingdoes CNV calling for each batch (or sequencing panel associated data set) separately. A text file with all .bam file paths for each batch and panel must be created.Hereis an example showing only one .bam file path. Multiple paths are separated with a newline. This file is usually an output ofclearCNV visualize_reassignment.c) The .bed-file for the sequencing panel for which this batch is put to CNV calling. An example can be foundhere. Note thatgeneis optimally replaced with the real name of the exon, gene or target.d) A k-mer alignability file in .bed format. Such files can be downloaded from UCSC (e.g. for Hg19here). A k-mer mappability track can also be created for example usingGenMap. In both cases the resulting Wig or BigWig files need to be converted to .bed to be used by clearCNV.notesThe chromosome name scheme in the reference and .bed-file should be of the forms: ChrX, chrX, X or Chr1, chr1, 1.CNV calling on chr X or chr Y: clearCNV automatically determines the copy number of the gonosomes. If your panel targets only a single gene there, it is better to delete according targets from the original .bed file to exclude them. It is necessary to have about double as many samples in your data set to enable meaningful CNV calling on the X or Y chromosomes with roughly equally many women and men in the samples.NOTEIf you do sample re-assignment on your own data, followed by CNV-calling, then only one metafile, one coverages file, and one bedfile will be used. This means that--metafile,--coveragesand--bedfileare given the same file paths in both workflow stepsclearCNV workflow_reassignmentandclearCNV visualize_reassignmentof clearCNV.Running ChecksChecks are automatically run on themasterbranch and pull requests.
Unit and integration tests are based on pytest and formatting is enforced with black.$maketestHistoryv0.0.1Everything is new!