# [R] BH correction with p.adjust

Scott Robinson Scott.Robinson at glasgow.ac.uk
Sun Jul 21 15:02:06 CEST 2013

```My understanding was that the vector was ranked, the adjusted p vector was calculated and then the vector is returned to the original order - I came across a stack overflow answer saying this:

Although the code there does not appear to be the same as when I type "p.adjust" into the command line. The order shouldn't matter anyway since my data was ordered by p.

Yesterday I tried a short example of 5 numbers and it seemed to work out though today I tried to do another short example to demonstrate that the order in the p vector you input doesn't matter but didn't quite get a working example this time. Maybe due to a rounding to first significant figure or something?

> smallP <- c(0.01, 0.5, 0.0001)
> names(smallP) <- c("first", "second", "last")
>
first second   last
2e-02  5e-01  3e-04
>
> 0.01*3/2
[1] 0.015
> 0.5*3/3
[1] 0.5
> 0.0001*3/1
[1] 3e-04

In any case I reconstructed a large example which can be run without real data where the figure is way off and definitely not the result of a rounding error:

> exampleP <- seq(from=0.0000001, to=0.1, by=0.00000001)
> length(exampleP)
[1] 9999991
>
>
> exampleP[1]
[1] 1e-07
>
> examplePBH[1]
[1] 0.1
>
> exampleP[1]*length(exampleP)/1
[1] 0.9999991

Any help with this would be very much appreciated. It seems like it ought to be such a simple and commonly used method and yet I am struggling and not sure what to do about it.

Thanks,

Scott

________________________________________
From: David Winsemius [dwinsemius at comcast.net]
Sent: 21 July 2013 03:33
To: Scott Robinson
Cc: r-help at r-project.org
Subject: Re: [R] BH correction with p.adjust

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
>>
> 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

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