Question: Snp - Quantitative Trait Association In A Gwa Study
gravatar for Agatha
7.6 years ago by
Agatha350 wrote:

I have a list of 700 snps and the associated genotypes for 8500 individuals. I am trying to analyze the association between the SNPs and two quantitative traits. ( => which snp is associated the most with each one of them).

I was considering to generate a linear regression model with each of the quantitative traits as Y variables, adjust by age and sex and then plot the log distribution of p values. (pvals for QT1) versus pvals for QT2).

regression QT1 : QT2, age, sex
regression QT2: QT1, age, sex

Is there a better approach/method/software tool in performing this type of analysis?

Thanks in advance.

gwas snp • 3.6k views
ADD COMMENTlink modified 7.4 years ago by yao.h.19880 • written 7.6 years ago by Agatha350
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7.6 years ago by
European Union wrote:

plink offers a fast approach to that kind of analysis with the parameters --qt-means and --GxE

ADD COMMENTlink written 7.6 years ago by

I have tried using plink for this , --assoc option , but I have only got the basic snp-qt association results. I have probably done something wrong when using --gxe returned only NA values...although I think I have used the correct input formats ..

ADD REPLYlink written 7.6 years ago by Agatha350
gravatar for David
7.6 years ago by
David740 wrote:

Using regression (either logistic, linear, generalised linear model or generalised least squares) is the traditional method to perform such association analysis. It is efficient and robust. The secret is in controlling for confounding factor while not over doing it. I used R for in the past for doing that. It's fast enough for a research environment. You have to control for multiple hypothesis testing at the end of course and decide for an FDR threshold.

An additional step after running the bare bone approach above is to look for epistasis events. This is computationally intensive but there are several software out there. For example:

EIP: (R package)

FastEpistasis: (PLINK extension)

ADD COMMENTlink written 7.6 years ago by David740
gravatar for yao.h.1988
7.4 years ago by
yao.h.19880 wrote:

If there may be some confounding factor such as population structured or related individual in your sample , I would recommended that to use mixed Linear model to correct them , some papers in Nature ( will introduced this method in GWAS

The other factor I think is important is that linear regression in GWAS often based on single marker regression,but we know SNPs are not independent, so it may loss something in this method.

Hope this help

ADD COMMENTlink written 7.4 years ago by yao.h.19880
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