The pre-process of QTL-GWAS colocalisation
ttongyyang opened this issue · 3 comments
Hi Chris,
I have learned to use the coloc you developed recently. It is a very useful tool. And I got some questions when I use this package.
When we use the coloc.abf() function, it needs full summary data from GWAS and QTL in our analysis region, but in many published studies, the researcher usually filters out non-significant loci (P > 1*10-8) from GWAS data before they conduct the coloc.abf, such as Xiong X, et al., Nat Genet., 2021(PMID: 34211177) and Li L, et al., Nat Genet., 2021(PMID: 34432052). I would like to ask whether we can filter out these non-significant loci, whether these loci are critical to affect our result in terms of finding causal genes. It would be greatly helpful for me.
Thank you!
Best regards
Yang Tong
Hi Chris,
We also noticed the same question. In many high-impact studies on molecular QTLs, researchers use coloc to analyze the colocalization of QTL loci with GWAS traits. Interestingly, many of these studies applied some cutoff to filter the QTL set or the GWAS trait set before the colocalization analysis. On the coloc website, it is recommended NOT to trim the SNP set by significance or MAF and to include ALL SNPs in that region. Since all of these studies applied a significance cutoff for the SNP set, I am curious if this is acceptable for coloc analysis.
Thank you.
Best,
Jiapei
Thanks for your quick reply. Really helpful!