HPexome 1.1.1

An automated tool for processing whole-exome sequencing data

An automated tool for processing whole-exome sequencing data

Whole-exome sequencing has been widely used in clinical applications for the identification of the genetic causes of several diseases. HPexome automates many data processing tasks for exome-sequencing data analysis of large-scale cohorts. Given ready-analysis alignment files it is capable of breaking input data into small genomic regions to efficiently process in parallel on cluster-computing environments. It relies on Queue workflow execution engine and GATK variant calling tool and its best practices to output high-confident unified variant calling file. Our workflow is shipped as Python command line tool making it easy to install and use.

Requirements

• BAM files must be sorted in coordinate mode. See sort bam files script.
• BAM files must have @RG tags with ID, SM, LB, PL and PU information. See fix rg tag script.

Example

The following command line takes a list of ready-analysis BAM files stored in alignment_files directory and reference genomes files (version b37). Then it breaks input data into smaller parts (--scatter_count 16) and submits to SGE batch system (--job_runner PbsEngine). All samples will be merged into a single VCF files (--unified_vcf) and output files will be written in result_files directory.

hpexome \
    --bam alignment_files \
    --genome references/b37/human_g1k_v37_decoy.fasta  \
    --dbsnp references/b37/dbsnp_138.b37.vcf \
    --indels references/b37/Mills_and_1000G_gold_standard.indels.b37.vcf \
    --indels references/b37/1000G_phase1.indels.b37.vcf \
    --sites references/b37/1000G_phase1.snps.high_confidence.b37.vcf \
    --sites references/b37/1000G_omni2.5.b37.vcf \
    --unified_vcf \
    --scatter_count 16 \
    --job_runner GridEngine \
    result_fies

For more information see http://bcblab.org/hpexome.