I use eigenstrat to correct population structure in my multiple GWAS. I want to calculate the genomic inflation factor before correction, I think GIF should be large, for population structure, but my GIF is too large, is 2.14! I never see so large GIF, even before correction, I do not know this may be something wrong with my work?
There are many reasons/artifacts that can be causing this. Starting from QC to the underlying genetics of your phenotype and the variants being tested. Are you using publicly availabe controls? What is the sample size? What kind of population structure do you have? It is hard to answer this question as there are many factors that can cause this.
A large GIF may mean you have made a calculation error, or it may mean you have a P value distribution that doesn't fit the normal GWA model for some reason. It could be correctly indicating that your data violate the population sub-structure assumptions normally made for a GWAS. If you "think the GIF should be large", then what makes you think that 2.14 is "too large"? I think substructure is only one form of bias that could cause a large GIF, though my understanding is it's the most typical cause. If you do a PCA on your genotypes, is there obvious structure, and can you relate that back to ethnicity or region?
You don't tend to see large GIF values in publications because a large GIF indicates there's something about the data that needs to be transformed or filtered before you can do the GWA analysis.
yes, when I use PCA to correct, the GIF is 1.02. What I am confused is that before correction, GIF too large is acceptable?
When you use logistic regression, you may also want to use maybe 3-4 PCAs as covariates.