Hi,
Can anybody help me about the odd output file yielded by the following command:
plink --noweb --allow-no-sex --bfile input_file --assoc --adjust --out output_file
In fact, I'd like to perform a simple Bonferroni basic association test, and I obtains the following output file (extract for first ten rows):
CHR SNP UNADJ GC BONF HOLM SIDAK_SS SIDAK_SD FDR_BH FDR_BY
1 rs7540001 INF INF INF INF INF INF INF INF
1 rs2743476 INF INF INF INF INF INF INF INF
1 rs9435653 INF INF INF INF INF INF INF INF
1 rs11810307 INF INF INF INF INF INF INF INF
1 rs12410470 INF INF INF INF INF INF INF INF
1 rs2873038 INF INF INF INF INF INF INF INF
1 rs1553451 INF INF INF INF INF INF INF INF
1 rs2580567 INF INF INF INF INF INF INF INF
1 rs11578605 INF INF INF INF INF INF INF INF
....
....
This file contains (528000 rows (SNPs)), in particular: 328 rows with BONF = "INF", and 1300 others rows with BONF < 0.05, the remaining SNPs present a higher BONF-value than 0.05. My question is: 1300+328 = 1628 (huge) is really the number of SNPs declared significants (<0.05)? Is it normal to get this kind of file ?
Thanks for you
1 answer
INF indicates an arithmetic overflow, which may not necessarily correspond to a significant SNP. (I'm curious whether PLINK 1.9 gives the same result, and whether it sorts them to the top of the file. This seems like a PLINK 1.07 bug to me.)
As for the other 1300, it is likely that you need to correct for population stratification: one way to get so many significant SNPs is if your phenotype is associated with membership in a particular subpopulation, and all of the SNPs in question are associated with that as well. Other forms of relatedness may also need to be accounted for. This is an active research area; look into "mixed-model association" with principal component covariates. (PLINK does not currently support this, but there are several other good software packages which do, and are capable of reading PLINK-format files.)
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Hi
I also have the same problem, did you solve that now?