This is a test version of Biostars. For the public version, visit https://www.biostars.org.
Phenotypic Variation Explained By Snps In Gwas

Thanks Genotypes group for really making it clear in a simple way. It was also interesting. I also want to ask one more question, how to calculate the variation explained by all the significant SNPs in combined, because tool I am using only calculating it for only individual SNP basis for a particular trait but some paper mentioning that all the significant SNPs contributed this % of variation for this trait. Can you please explain. Thanks,

Vinod

snp
• 6,764 views • link
updated by Joey Joey • written by kumar.vinod81 kumar.vinod81

1 answer

Which paper? Unless you mention the paper, it is very hard to figure out exactly what they did.

Just a guess: Do you know what the significant SNPs are for your analysis? If yes, why don't you make a dataset with the significant genes only and then use the GCTA s/w (http://www.complextraitgenomics.com/software/gcta/) to calculate phenotypic variation?

• 0 views • link
written by Joey Joey

HI Joey, I am not getting how to calculate contribution of all the significant SNPs to a particular trait. Below some papers mentioned such analysis http://www.nature.com/ng/journal/v42/n11/full/ng.695.html#/supplementary-information http://www.nature.com/ncomms/journal/v2/n9/full/ncomms1467.html
I've almost done all of the analysis like significant SNPs for all of the traits but I am totally confused at this step on SNP contribution to phenotypic variation. Can you please help? Thanks,

• 0 views • link
written by kumar.vinod81 kumar.vinod81

Hello vinod,

Were you able to find the answer to your question? if yes, can you please give detail of the tool and steps used for the same?

• 1 views • link
written by Tm Tm

you can fit multiple linear regression in R by fitting all the significant SNPs (vector in R) as explanatory variable while the trait of interest (vector in R) as a response variable.

• 1 views • link
written by kumar.vinod81 kumar.vinod81

Thank you for the reply. But, my main concern is obtaining the phenotypic variance (var %) using the gwaa.R (GenABLE) result which I have for each trait separately. It contains 5 columns as shown below:

  • SNP
  • Estimate
  • Std.Error
  • t-value
  • p-value

i.e I got the list of significant SNPs aasociated with particular trait using gwaa.R which uses GLM approach but, now I am interested in knowing whether these significant loci responds to that particular trait or not. Thus want to get phenotypic variance (R2). So which package can I use further to reach my goal? Please correct me if you feel I am on wrong track.

• 1 views • link
written by Tm Tm

Log in to answer this question.

More posts like this