Hi everyone, I am doing a study and I would like to cross methylation data (coming from Reduced representation bisulfite sequencing for now, but we plan to do it on the whole genome) with genomic SNPs (illumina) from 2 different populations of the same species (one population isolated, the other large). By following the classical pipeline I arrived at a vcf file for each individual containing the SNPs compared to the reference genome.
How can I tell which SNPs are unique to the isolated population compared to the large population? Is there then a way to extract only the SNPs involved in the CpG context?
Thanks a lot for the help
1 answer
What is the "classical pipeline"? If you use a tool like GATK, you can call variants in cohorts which can be more useful for population genomic work. See this page for information and a link to their best practices.
If you want to keep the existing individually called SNPs, you can try to merge all the VCFs into a single population/experiment wide file. In either case, it's a matter or parsing the GT field for each variant locus. If using R, you can read in vcfs using the library vcfR. Or use a population genomics library like PopGenome.
And yes, if you analysed methylation state using a different tool, say methylKit for example, you can then compare the site column in the VCFs to identify SNPs within n bp of a methylation site. Lots of different functions and libraries would be useful, including subset, data.table::foverlaps, and GRanges.
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