Hi,

There is a question that I am confused.
 I have a set of data like this:

hsa-miR-205--GATA3    0.797882767 1.08E-13
hsa-miR-205--ITGB4     0.750217593 1.85E-11
hsa-miR-187--PGF        0.797604155 3.24E-11
hsa-miR-205--SERPINB5 0.744124886 3.28E-11
hsa-miR-205--PBX1 0.734487224 7.89E-11
hsa-miR-205--MCC 0.72499934 1.80E-10
hsa-miR-205--WNT5B 0.717705259 3.33E-10
hsa-miR-200c--PKN2 0.721746815 3.46E-10
hsa-miR-200c--PCYOX1 0.721698034 3.48E-10
hsa-miR-200c--WDR68 0.72068017 3.78E-10

And I want to do the Benjamini & Hochberg correction.

So I run :

rm(list=ls())
a<-read.csv("1-correlation.txt",sep="\t",header=F,quote="")
c<-p.adjust(a$V3,"BH")
a[,4]<-c
write.table(a,"zz.txt",sep="\t")

And I got the result:

hsa-miR-205--GATA3 0.797882767 1.08E-13 1.08E-12
hsa-miR-205--ITGB4 0.750217593 1.85E-11 8.20E-11
hsa-miR-187--PGF 0.797604155 3.24E-11 8.20E-11
hsa-miR-205--SERPINB5 0.744124886 3.28E-11 8.20E-11
hsa-miR-205--PBX1 0.734487224 7.89E-11 1.58E-10
hsa-miR-205--MCC 0.72499934 1.80E-10 3.00E-10
hsa-miR-205--WNT5B 0.717705259 3.33E-10 3.78E-10
hsa-miR-200c--PKN2 0.721746815 3.46E-10 3.78E-10
hsa-miR-200c--PCYOX1 0.721698034 3.48E-10 3.78E-10
hsa-miR-200c--WDR68 0.72068017 3.78E-10 3.78E-10

When I check it, I found some adjust pvalue are not same to result that I
did manually.

Can anyone help for this. Thanks,

Jiang

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