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How to calculate proportion of phenotypic variance explained by significant SNP in GWAS results

I am conducting GWAS using GAPIT R package with FarmCPU model. However, unlike GLM and MLM, GAPIT does not produce R2 when FarmCPU model is used. I tried to work around this by using the linear model function in R (lm) like this: fit<-lm(trait~SNP, data=mydata) but I am not sure if this is correct because I got R2=0 for some SNPs with very significant GWAS signals! I have seen hierGWAS package which gives R2 for cluster of SNPs but not single SNP. I appreciate your suggestions on this and thank you for your time.

gwas farmcpu phenotypic variance snp

1 answer

Anyone interested in this question, I found the answer in this article: https://doi.org/10.3389/fgene.2019.00302

Thanks for coming back to provide an update. Is it possible to paraphrase/summarize the solution to provide additional utility? You can edit the post above and add that information.

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