[BioC] [BioC} Multiple testing correction

[James W. MacDonald]

Hi Lucia,

On 1/7/2011 2:52 PM, Lucia Peixoto wrote:
> Hi
>
> I was having some issues with the p-values of differential expression of my
> samples using SAM, so I to compare with more traditional multiple testing
> approaches
> I thought I will just do a ttest and then use p.adjust to get  BH corrected
> pvalues
> My input is just a two column textfile where the first column is the Affy
> probe IDs and the second is the ttest pvalue
> All I get out is the same p-values I put in, since I am a pretty naive R
> programmer I am sure there is something simple I am doing wrong
>
> help will be greatly appreciated, thanks!!
>
> here is my script:
>
> Data<-read.table("input", header=TRUE, row.names=1)
> p.adj<- p.adjust(Data, method = "BH", n= length (Data))
> write.table(p.adj, file="output", sep="\t")

 From ?p.adjust

Usage:

      p.adjust(p, method = p.adjust.methods, n = length(p))

      p.adjust.methods
      # c("holm", "hochberg", "hommel", "bonferroni", "BH", "BY",
      #   "fdr", "none")

Arguments:

        p: vector of p-values (possibly with 'NA's).

You are passing in a data.frame where the second column contains the 
p-values, and expecting R to figure that out. Which it won't be able to do.

Try

Data[,2] <- p.adjust(Data[,2])
write.table(Data, "output", sep = "\t")

Best,

Jim


>
> My output is identical to my input
>
> 	[[alternative HTML version deleted]]
>
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-- 
James W. MacDonald, M.S.
Biostatistician
Douglas Lab
University of Michigan
Department of Human Genetics
5912 Buhl
1241 E. Catherine St.
Ann Arbor MI 48109-5618
734-615-7826
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