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

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,

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?

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.

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:

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.

Really didn't understand, exactly what you want to do? In GenABEL, its really tough to get r2 directly. You can follow this link http://forum.genabel.org/search.php?keywords=phenotypic+variance+explained+by+SNP for more clarity. Or you can deleted the most significant SNP and then see the difference in h2 between whole set and deleted SNP set. Thanks,