Hi,
I am running quality control (sex discrepancy) on my binary plink files. I am new to GWAS and PLINK in general so I am not really sure about what to do in the following:
I used the command plink --bfile file_name --check-sex and found one individual with
PEDSEX: 2, SNPSEX: 0, status: PROBLEM, and F: 0.2303. I was following a GWAS/quality control manual i found online, and removed that individual form my binary files using --remove.
I then used --impute-sex and realized I brought back the individual to my dataset, now with
PEDSEX: 0, SNPSEX: 0, status: PROBLEM, and F: 0.2303.
(1) Is the impute-sex step necessary? If all the statuses of the other individuals were 'OK', would --impute-sex do anything to those individuals? (2) Should I proceed to the next QC step right after removing that one individual, and not use --impute-sex at all?
Thank you very much!
Hello, Thank you very much for your reply. I have been trying to find different later protocols for the past two weeks but realize there is a wide variety of approaches and thresholds.... I see that a lot of GWAS papers referring back to the Anderson et al., 2010 paper (Data quality control in genetic case-control association studies), but I'm worried about it not being the most updated either. I then found this PDF (https://cran.r-project.org/web/packages/plinkQC/vignettes/plinkQC.pdf ) from the R website that was written in 2019 March, which I believe should be more applicable... I was wondering if you may have any recommendations/suggestions on some starters/articles which I could look up for more background and updates about GWAS QC. Thank you once again! I really appreciate it.