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Asked: 2026-06-15T09:30:20+00:00

I have a data.frame with an id field and three different and unrelated p-values.

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I have a data.frame with an id field and three different and unrelated p-values. I would like to apply the benjamini-hochberg corection at each column.
I’ve been working with the p.adjust as function p.adjust(data[,2], "BH"), but I’m having trouble since I have to sort each column before applying the correction and I lose the id information after that. My data looks like:

id  p1  p2  p3
1   ENSG00000179094 1.000000e+00    1.000000e+00    1.000000e+00
2   ENSG00000164306 1.000000e+00    1.000000e+00    1.000000e+00
3   ENSG00000147180 1.000000e+00    8.778847e-02    1.000000e+00
4   ENSG00000172932 4.370119e-01    1.766703e-04    1.000000e+00
5   ENSG00000137252 1.000000e+00    2.562124e-02    1.000000e+00
6   ENSG00000144644 1.654108e-02    1.000000e+00    1.000000e+00
7   ENSG00000197273 3.316301e-01    5.341301e-01    1.000000e+00
8   ENSG00000169221 1.000000e+00    1.000000e+00    1.000000e+00
9   ENSG00000108309 8.689368e-01    2.350522e-03    1.000000e+00
10  ENSG00000172382 1.000000e+00    9.028471e-01    2.697276e-02
11  ENSG00000099937 1.000000e+00    1.000000e+00    9.988716e-01
12  ENSG00000259431 1.000000e+00    1.000000e+00    7.268023e-01
...

Is there an easiest way or package to do this without losing the information from the id’s?

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1 Answer

  1. Editorial Team

    You can use numcolwise , apply a function to only numeric columns of a data.frame.

    library(plyr) 
 cbind(dat$id,numcolwise(p.adjust)(dat))
             dat$id       p1          p2        p3
1  ENSG00000179094 1.000000 1.000000000 1.0000000
2  ENSG00000164306 1.000000 1.000000000 1.0000000
3  ENSG00000147180 1.000000 0.790096230 1.0000000
4  ENSG00000172932 1.000000 0.002120044 1.0000000
5  ENSG00000137252 1.000000 0.256212400 1.0000000
6  ENSG00000144644 0.198493 1.000000000 1.0000000
7  ENSG00000197273 1.000000 1.000000000 1.0000000
8  ENSG00000169221 1.000000 1.000000000 1.0000000
9  ENSG00000108309 1.000000 0.025855742 1.0000000
10 ENSG00000172382 1.000000 1.000000000 0.3236731
11 ENSG00000099937 1.000000 1.000000000 1.0000000
12 ENSG00000259431 1.000000 1.000000000 1.0000000

    To use other arguments:

    cbind(dat$id,numcolwise(p.adjust)(dat, method = 'bonferroni', n = 20))
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