bed_to_tabix

bed_to_tabix will download a gzipped VCF file with the 2,504 genotypes from The 1,000 Genomes Project in the regions defined in one or more BED files. The program will specifically handle the BED sorting, the merging of many BEDs, the parallel-downloading of the different chromosome variants with tabix from different URLs (one per chromosome in the BED regions), and it will merge the resulting VCFs in a single gzipped VCF. You end up with a single multi-chromosome multi-sample merged gzipped VCF with all 1KG genotypes in the regions that you want.

Requirements

• A working Internet connection.
• Python 3.6 or greater (you can get it at Anaconda).
• tabix, bgzip, bcftools, gatk3, java (for GATK). You can download the first three from htslib.org, choosing the htslib and bcftools packages. If you have an old tabix version, update it because the command line interface changed from older versions. GATK3 can be downloaded from their GitHub, and it requires Java to run. If you're in bioinformatics, you will likely have all of these programs already installed.
• A human reference genome in fasta format for GATK3 to run. Instructions to get it working here.

How to Install bed_to_tabix

Clone this repo and install the package:

git clone https://github.com/biocodices/bed_to_tabix
cd bed_to_tabix
python setup.py install

Usage

I'm not sure if there's any risk of getting banned if you perform too many parallel downloads from 1kG servers, so experiment with --threads at your own risk.

# Download the regions in regions1.bed to regions1.vcf.gz
bed_to_tabix --in regions1.bed

# Download the regions in regions1.bed, 10 downloads at a time, to 1kg.vcf
bed_to_tabix --in regions1.bed --threads 10 --unzipped --out 1kg

# Download the regions in both bed files to regions1__regions2.vcf.gz
bed_to_tabix --in regions1.bed --in regions2.bed

You will get a [gzipped] VCF file with the 1kG variants found in your regions.

In case you can't connect to port 21 (FTP) --I know this is usual in some University networks--, you can use the HTTP URLs from 1000 Genomes:

# Download from the HTTP URLs in case your traffic to FTP is blocked
bed_to_tabix --in regions1.bed --http

For devs

Contributions are welcome! To run the small test suite:

pytest -q bed_to_tabix/test