- Download the Dockerfile and inside same directory run:
docker build -t <IMAGE_TAG> .
- Check the IMAGE ID (look for the name of your image tag):
docker images -a
- Start container
docker run --name <CONTAINER_NAME> -it <IMAGE_ID> bash
- Copy your files to container
docker cp <DIRECTORY/FILES> <CONTAINER_ID>:<DIRECTORY>
Steps:
Input: sam files.
1 - Converts sam files to bam files
2 - Creates indexed bam files (bai) with samtools
3 - Performs variant calling with freebayes using a reference genome. It results in vcf files
4 - These files are compressed using bgzip and indexed using tabix
5 - Filter variants considering MAF, Hardy-Weinberg Equilibrium & missing variants proportion with Plink. This step generates a bed file
6 - Converts bed file back to vcf format also using Plink
7 - Compress and index filtered vcf files as in step 4
8 - Get the common variants considering all individuals of same family with bedtools isec
9 - Load the files with common SNPs of each family on R and analyse it (Venn graph and comparisons between families)
snakemake -s variantCalling -c 50