Hello,
I have a data frame which looks like this:
> head(a,20)
rs pvalue
1: rs185642176 0.267407
2: rs184120752 0.787681
3: rs10904045 0.508162
4: rs35849539 0.875910
5: rs141633513 0.787759
6: rs4468273 0.542171
7: rs4567378 0.539484
8: rs7084251 0.126445
9: rs181605000 0.787838
10: rs12255619 0.192719
11: rs140367257 0.788008
12: rs10904178 0.969814
13: rs7918960 0.436341
14: rs61688896 0.526256
15: rs151283848 0.787284
16: rs140174295 0.989107
17: rs145945079 0.787015
18: rs4881370 0.455089
19: rs183895035 0.787015
20: rs181749526 0.787015
> dim(a)
[1] 3859763 2
What I would like to do is to take random subsets of 30 of those rs
throughout the dataframe and find out which subsets of those generated
have FDR value <0.05
FDR I would calculate I guess with:
a$fdr=p.adjust(a$pvalue,method="BH")
but I also guess I would be calculating only FDR for a particular
subset of 30 randomly chosen rs, not for the whole data set.
The result I would like to present like in the attached plot. The
x-axis say proportion of SNPs and in my case SNP is equivalent to rs
Can you please help with this, I really don't have idea how to go about this.
Thanks
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