Extracting covariate effects from the model

[sonalkumarr]

Hi, I am interested in understanding the effects of covariates (effect size, associated p-value, etc) for the model that's run in permGWAS. I understand it might be hard to do that given there can be so many loci being tested, but what about an overall effect seen for the genotype matrix in the model?

[MauraJohn]

Hi, thanks a lot for the suggestion!
We'll take a look into it, but just a heads-up: things are a bit busy on our end over the next few weeks, so it might take us a little while to get to it.

[sonalkumarr]

No worries, thank you for your response! Just to provide you with a little bit more context: I am also extracting significant SNPs identified by the GWAS result and studying the role of different genotypes for the phenotype under study. It would be really neat if it was possible to understand if any of the covariates have a significant effect (and to what extent, i.e., the effect size) on the phenotype I'm studying at the genome-wide level (which is where the overall model summary like the one I asked about in the issue I raised comes in), instead of just at the SNP level when I am running a linear model to understand what's going on.