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Post by kevinanderson on Jan 8, 2020 19:01:50 GMT
Hi All,
Thanks for the fastGWA method and resource!
I'm analyzing UKB imputed data with fastGWA have a question about generating the sparse GRM. Assuming I'm working with properly QC'd imputed data (i.e. MAF/INFO/etc.), do you recommend making the initial GRM using the GREML-LDMS approach (partitioning GRMs by LD; cnsgenomics.com/software/gcta/#GREMLinWGSorimputeddata)?
Or would it be preferable to use a GRM created from directly genotyped/non-imputed calls?
I'm assuming that creating a GRM from imputed data without accounting for LD not ideal, but please let me know if I'm mistaken!
Thank you! Kevin
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anbai
New Member
Posts: 4
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Post by anbai on Sept 1, 2021 12:38:28 GMT
Did you have a solution here? I am facing the same dillema.
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