ContextSV

A long-read, whole-genome structural variant (SV) caller. It takes as input long read alignments (BAM), the corresponding reference genome (FASTA), a VCF with high-quality SNPs (e.g. via GATK, Deepvariant, NanoCaller, and gnomAD database VCF files with SNP population frequencies for each chromosome. Class documentation is available at https://wglab.openbioinformatics.org/ContextSV

Installation

Building from source (for testing/development)

ContextSV requires HTSLib as a dependency that can be installed using Anaconda. Create an environment containing HTSLib:

conda create -n htsenv -c bioconda -c conda-forge htslib
conda activate htsenv

Then follow the instructions below to build ContextSV:

git clone https://github.com/WGLab/ContextSV
cd ContextSV
make

ContextSV can then be run:

./build/contextsv --help

Usage: ./build/contextsv [options]
Options:
  -b, --bam <bam_file>          Long-read BAM file (required)
  -r, --ref <ref_file>          Reference genome FASTA file (required)
  -s, --snp <vcf_file>          SNPs VCF file (required)
  -o, --outdir <output_dir>     Output directory (required)
  -c, --chr <chromosome>        Chromosome
  -r, --region <region>         Region (start-end)
  -t, --threads <thread_count>  Number of threads
  -h, --hmm <hmm_file>          HMM file
  -n, --sample-size <size>      Sample size for HMM predictions
     --min-cnv <min_length>     Minimum CNV length
     --eps <epsilon>             DBSCAN epsilon
     --min-pts-pct <min_pts_pct> Percentage of mean chr. coverage to use for DBSCAN minimum points
  -e, --eth <eth_file>          ETH file
  -p, --pfb <pfb_file>          PFB file
     --save-cnv                 Save CNV data
     --debug                    Debug mode with verbose logging
     --version                  Print version and exit
  -h, --help                    Print usage and exit

Downloading gnomAD SNP population frequencies

SNP population allele frequency information is used for copy number predictions in this tool (see PennCNV for specifics). We recommend downloading this data from the Genome Aggregation Database (gnomAD).

Download links for genome VCF files are located here (last updated April 3, 2024):

• gnomAD v4.0.0 (GRCh38): https://gnomad.broadinstitute.org/downloads#4

• gnomAD v2.1.1 (GRCh37): https://gnomad.broadinstitute.org/downloads#2

Script for downloading gnomAD VCFs

download_dir="~/data/gnomad/v4.0.0/"

chr_list=("1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" "13" "14" "15" "16" "17" "18" "19" "20" "21" "22" "X" "Y")

for chr in "${chr_list[@]}"; do
    echo "Downloading chromosome ${chr}..."
    wget "https://storage.googleapis.com/gcp-public-data--gnomad/release/4.0/vcf/genomes/gnomad.genomes.v4.0.sites.chr${chr}.vcf.bgz" -P "${download_dir}"
done

Finally, create a text file that specifies the chromosome and its corresponding gnomAD filepath. This file will be passed in as an argument:

gnomadv4_filepaths.txt

1=~/data/gnomad/v4.0.0/gnomad.genomes.v4.0.sites.chr1.vcf.bgz
2=~/data/gnomad/v4.0.0/gnomad.genomes.v4.0.sites.chr2.vcf.bgz
3=~/data/gnomad/v4.0.0/gnomad.genomes.v4.0.sites.chr3.vcf.bgz
...
X=~/data/gnomad/v4.0.0/gnomad.genomes.v4.0.sites.chrX.vcf.bgz
Y=~/data/gnomad/v4.0.0/gnomad.genomes.v4.0.sites.chrY.vcf.bgz

Revision history

For release history, please visit here.

Getting help

Please refer to the contextSV issue pages for posting your issues. We will also respond your questions quickly. Your comments are critical to improve our tool and will benefit other users.