[R] BH correction with p.adjust

[David Winsemius]

On Jul 20, 2013, at 10:37 AM, Scott Robinson wrote:

> Dear List,
> 
> I have been trying to use p.adjust() to do BH multiple test correction and have gotten some unexpected results. I thought that the equation for this was:
> 
> pBH = p*n/i

Looking at the code for `p.adjust`, you see that the method is picked from a switch function

lp <- length(p)
BH = {
        i <- lp:1L
        o <- order(p, decreasing = TRUE)
        ro <- order(o)
        pmin(1, cummin(n/i * p[o]))[ro]
    }

You may not have sorted the p-values in pList.


> 
> where p is the original p value, n is the number of tests and i is the rank of the p value. However when I try and recreate the corrected p from my most significant value it does not match up to the one computed by the method p.adjust:
> 
>> setwd("C:/work/Methylation/IMA/GM/siteLists")
>> 
>> hypTable <- read.delim("hypernormal vs others.txt")
>> pList <- hypTable$p
>> names(pList) <- hypTable$site
>> 
>> adjusted <- p.adjust(pList, method="BH")
>> adjusted[1]
> cg27433479 
> 0.05030589 
>> 
>> pList[1]*nrow(hypTable)/1
> cg27433479 
> 0.09269194 
> 

No data provided, so unable to pursue this further.

> I tried to recreate this is a small example of a vector of 5 p values but everything worked as expected there. I was wondering if there is some subtle difference about how p.adjust operates? Is there something more complicated about how to calculate 'n' or 'i' - perhaps due to identical p values being assigned the same rank or something? Does anyone have an idea what might be going on here?


-- 

David Winsemius
Alameda, CA, USA