rhshah/detect_hotspot_sv

Filtering Delly Raw results for Hotspots

detect_hotspot_sv.py

Look for potential hotspot structural variants by applying filters to all SVs called by DELLY.

Some code adapted from Ronak Shah's check_cDNA_contamination.py.

Usage:

usage: detect_hotspot_sv.py [-h] [-s sample_name] [-t n] [-hsl hotspot_list]
                            [-bl black_list] [-kgl keep_genes]
                            [--iAnnotateSV iAnnotateSV.py]
                            [--genome {hg18,hg19,hg38}]
                            structural_variants.vcf /path/to/output_directory/

positional arguments:
  structural_variants.vcf
                        VCF with deletion event calls
  /path/to/output_directory/
                        Directory to put output in

optional arguments:
  -h, --help            show this help message and exit
  -s sample_name, --sample-name sample_name
                        Prefix [default: filename of in_vcf]
  -t n, --threshold n   Output must have at least this many qualifying PE
                        support. [default: 1]
  -hsl hotspot_list, --hotspotFile hotspot_list
                        path to list of hotspots
  -bl black_list, --blackListGenes black_list
                        path to list of black list genes File
  -kgl keep_genes, --genesToKeep keep_genes
                        path to list of genes to keep file
  --iAnnotateSV iAnnotateSV.py
                        path to iAnnotateSV.py script [default: /home/shahr2/g
                        it/iAnnotateSV/iAnnotateSV/iAnnotateSV.py]
  --genome {hg18,hg19,hg38}
                        Reference genome version to use during annotation
                        [default: hg19]
					

Example usage:

$ python detect_hotspot_sv.py example.vcf ./ -s my_sample -hsl /path/to/hotspotlist -kgl /path/to/geneToKeep -bl /path/to/blacklist

Output:

• <output directory>/<sample name>.hotspot_sv_final.txt: a one-line, tab-delimited list of sample name and its structural variants
• Intermediate files in <output directory>/scratch/

Requires:

• Python 2
• pandas
• gridmap
• iAnnotateSV and its required modules
• iCallSV
• PyVCF

Script process

1. Filter the input VCF for any events occuring i defined hotspots
2. Convert the filtered VCF to tab-delimited input format for iAnnotateSV, using iCallSV.dellyVcf2Tab
3. Annotate using iAnnotateSV
4. Merge Annotation with VCF with iCallSV.mergeFinalFiles
5. Filter merged files with iCallSV.fiterAnnotatedSV

run_detect_hotspot_sv_analysis.py

Wrapper to run detect_hotspot_sv.py

Usage:

python run_detect_hotspot_sv_analysis.py  -h

usage: run_detect_hotspot_sv_analysis.py  [options]

Run processed-psuedogene_analysis on selected pools/samples using MSK data

optional arguments:
  -h, --help            show this help message and exit
  -mif folders.fof, --metaInformationFile folders.fof
                        Full path folders and sample names of files.
  -qc /some/path/qcLocation, --qcLocation /some/path/qcLocation
                        Full path qc files.
  -P /somepath/python, --python /somepath/python
                        Full path Pyhton executables.
  -dhs /somepath/detect_hotspot_sv.py, --detecthotspotsv /somepath/detect_hotspot_sv.py
                        Full path processpsuedogene.py executables.
  -ias /somepath/iAnnotateSV.py, --iAnnotateSV /somepath/iAnnotateSV.py
                        Full path iAnnotate.py executables.
  -q all.q or clin.q, --queue all.q or clin.q
                        Name of the SGE queue
  -qsub /somepath/qsub, --qsubPath /somepath/qsub
                        Full Path to the qsub executables of SGE.
  -t 5, --threads 5     Number of Threads to be used to run process-psuedogene
                        analysis on
  -v, --verbose         make lots of noise [default]
  -o /somepath/output, --outDir /somepath/output
                        Full Path to the output dir.
  -hsl hotspot_list, --hotspotFile hotspot_list
                        path to list of hotspots
  -bl black_list, --blackListGenes black_list
                        path to list of black list genes File
  -kgl keep_genes, --genesToKeep keep_genes
                        path to list of genes to keep file

Example usage:

$ python run_detect_hotspot_sv_analysis.py  -mif /location/to/meatdata.txt -qc /dmp/qc/location/path -dhs /path/to/detect_hotspot_sv.py -ias /path/to/iAnnotateSV.py -q sge_queue_name -qsub path/to/qsub -t 1 -o /path/to/output/directory -v -hsl /path/to/hotspotlist -kgl /path/to/geneToKeep -bl /path/to/blacklist

Meta information file format

Tab separated file with header:

Run	MRN	Mnumber	LIMS_ID	DMP_ASSAY_ID	12245
PoolName	SomeID	SomeID	SomeID	SomeID	Flag(0,1)

From here: The Run and LIMS_ID are required.