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I'm considering conducting a GWAS analysis using the UK Biobank data, which involves a very large cohort of 500,000 participants. In our lab, we've previously used the Hail software for GWAS analysis. However, when I explore research papers that have conducted GWAS using UK Biobank data, it seems like BOLT-LMM is the more commonly used tool, sometimes SAIGE or regenie.
My question is: I wonder if using Hail is enough for GWAS with a very large cohort, or if it would be better to use tools like BOLT-LMM. What are the pros and cons of these tools?
I don't know much about BOLT-LMM, SAIGE, and regenie except that they can analyze very large cohorts. If using Hail is sufficient, I would like to keep using Hail since it will save the time and effort of installing and learning how to use new tools.
1 answer
Usually it boils down to trade accuracy for speed. There is a nice comparison of several tools like Regenie, BOLT-LMM and others in this method LDAK-KIV, Regenie, BOLT-LMM
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