Question
Asked 2nd Jan, 2020

How to determine the percent phenotypic variation explained (PVE) by a selected SNP?

Can anyone suggest a way to calculate PVE of selected SNPs in a GWA panel?
I know that some software (such as GAPIT) provide PVE as an output but I used EMMAX (which does not) to run the GWAS and I was wondering if there are alternative ways to calculate it...

Popular Answers (1)

8th Jan, 2020
Elena Feofanova
University of Texas Health Science Center at Houston
Hello,
You can do so in the software of your choice using the formula:
Proportion of variance in phenotype explained by a given SNP (PVE) = [2*(beta^2)*MAF*(1-MAF)]/[2*(beta^2)*MAF(1-MAF)+((se(beta))^2)*2*N*MAF*(1-MAF)]
where:
N - sample size
se(beta) - standard error of effect size for the genetic variant of interest
beta - effect size for the genetic variant of interest
MAF - minor allele frequency for the genetic variant of interest
it is described in:
Shim, H., Chasman, D.I., Smith, J.D., Mora, S., Ridker, P.M., Nickerson, D.A., Krauss, R.M., and Stephens, M. (2015). A multivariate genome-wide association analysis of 10 LDL subfractions, and their response to statin treatment, in 1868 Caucasians. PLoS One 10, e0120758.
Supplementary Information: S1: Computing proportion of variance in phenotype explained by a given SNP (PVE).
3 Recommendations

All Answers (3)

8th Jan, 2020
Elena Feofanova
University of Texas Health Science Center at Houston
Hello,
You can do so in the software of your choice using the formula:
Proportion of variance in phenotype explained by a given SNP (PVE) = [2*(beta^2)*MAF*(1-MAF)]/[2*(beta^2)*MAF(1-MAF)+((se(beta))^2)*2*N*MAF*(1-MAF)]
where:
N - sample size
se(beta) - standard error of effect size for the genetic variant of interest
beta - effect size for the genetic variant of interest
MAF - minor allele frequency for the genetic variant of interest
it is described in:
Shim, H., Chasman, D.I., Smith, J.D., Mora, S., Ridker, P.M., Nickerson, D.A., Krauss, R.M., and Stephens, M. (2015). A multivariate genome-wide association analysis of 10 LDL subfractions, and their response to statin treatment, in 1868 Caucasians. PLoS One 10, e0120758.
Supplementary Information: S1: Computing proportion of variance in phenotype explained by a given SNP (PVE).
3 Recommendations
6th Jul, 2020
Ahmed Warsame
John Innes Centre
Hi Giovanni Melandri I am in the same situation where the R package (rMVP) for GWAS is not giving me effect size and se for all SNPs but p-values. So, I would like to know if you got a solution that you can share.
I don't think I can apply the answer by Elena Feofanova
Thanks.

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