On Apr 14, 2012, at 11:40 AM, Junyu Lee wrote:
Hello everyone,
I have a data frame (tt), see below (I only show 2 genes, actually I
have a
lot):
Shouldn't you be working with a statistician to get advice about how
to handle the multiple comparison issues you are most certainly facing?
--
David.
group gene1 gene2 Control 28.9776 9.9355
Control 28.9499 10.0997 Control 29.5468 14.2995 Control 29.5246
13.9561
Test1 29.1864 9.7718 Test1 29.2048 10.0388 Test1 34.9563 11.9509
Test1
34.9464 11.8909 Test2 36.9566 14.5316 Test2 37.1309 14.5188 Test2
36.1017
29.5468 Test2 36.0883 29.5246
I'd like to calculate p values: Test1 vs Control and Test2 vs Control
respectively for Gene1. Similar calculate performed for Gene2.
I tried:
sapply(levels(fac), function(x) t.test(tt1$gene1,
tt$gene1[which(fac==x)])$p.value) # I don't really understand how it
works, I copied from genefilter.
where: fac=as.factor(tt$group)
It seemed to work for first column. I don't know how to use apply()
to
make it work on rest of column because I used tt$gene1 specifically.
Or
whatever method that works
Thank you in advance.
Junyu
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