I would like to perform genotype-phenotype-environment association studies along gradients (continuous allele/phenotype change) using low-coverage WGS data (~100 individuals, mean sequencing depth: 1.18). Calling/genotyping accuracy with such a low coverage remain challenging. In my non-model study system, LD decays relatively fast, likely limiting the application of approaches based on leveraging linkage information (e.g., SNPtools, EXL-WGS). In addition, allele frequency changes continuously along the gradient; variant calling "by population/deme" would lead to loss of precious information. Any suggestion on how to best call variants (and genotypes) with this data?
Hello, see attached info may be useful for you.
Good luck!
Thank you very much Karen A. Darbinyan, very useful. These studies analyse data by population, while I have a continuous allele change along a gradient; I would loose precious information if I subdivide my samples in "demes". Any suggestion for continuous genomic data?
Yes, some losses in precision of continuous change allele change, for more precise calculation you can use some statistics perform calculation of variances.
see link below also good info.
https://www.cell.com/cell-systems/fulltext/S2405-4712(18)30240-0?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS2405471218302400%3Fshowall%3Dtrue
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