Phenotypic Variation Explained By Snps In Gwas
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11.3 years ago
kumar.vinod81 ▴ 330

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

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11.3 years ago
Joey ▴ 430

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?

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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,

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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?

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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.

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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.

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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,

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