p-value adjustment
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Wenbin Liu ▴ 100
@wenbin-liu-943
Last seen 9.6 years ago
Dear list, I'm puzzled by the R function p.adjust with NA values in the first argument. The adjustment gives different result with and without the NAs. The question then is, which approach should one take: with or without NAs in the first argument? Thanks a lot! Wenbin
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@gordon-smyth
Last seen 4 hours ago
WEHI, Melbourne, Australia
>Wenbin Liu wnbnl at yahoo.com >Wed Mar 23 23:51:28 CET 2005 > >Dear list, > >I'm puzzled by the R function p.adjust with NA values >in the first argument. The adjustment gives different >result with and without the NAs. Please refer to the extensive recent discussion on this topic on the R-devel mailing list. > The question then is, >which approach should one take: with or without NAs in >the first argument? The limma package functions remove NAs before using p.adjust(), and I believe this is virtually always correct in the microarray context. Gordon >Thanks a lot! > >Wenbin
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@matthew-hannah-621
Last seen 9.6 years ago
One thing to add on this point that might be of interest is that an initial look at p.adjust p.adjust(p, method = p.adjust.methods, n = length(p)) would suggest that including NAs would result in more conservative correction as n > # of p-values, but it doesn't (at least for fdr) as the NAs are ordered below the minimum p-value from your vector in the calculation. So if you fdr correct with the NAs present then you get more significant p-values than you should and the results are meaningless - and there's no error message. Obviously, the nice work by the developers will correct this. >>Wenbin Liu wnbnl at yahoo.com >>Wed Mar 23 23:51:28 CET 2005 >> >>Dear list, >> >>I'm puzzled by the R function p.adjust with NA values >>in the first argument. The adjustment gives different >>result with and without the NAs. > >Please refer to the extensive recent discussion on this topic on the >R-devel mailing list. > >> The question then is, >>which approach should one take: with or without NAs in >>the first argument? > >The limma package functions remove NAs before using p.adjust(), and I >believe this is virtually always correct in the microarray context. > >Gordon > >>Thanks a lot! >> >>Wenbin
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Wenbin Liu ▴ 100
@wenbin-liu-943
Last seen 9.6 years ago
Thanks Matthew and Gordon for your comments. Wenbin --- Matthew Hannah <hannah@mpimp-golm.mpg.de> wrote: > One thing to add on this point that might be of > interest is that an > initial look at p.adjust > p.adjust(p, method = p.adjust.methods, n = > length(p)) > would suggest that including NAs would result in > more conservative > correction as n > # of p-values, but it doesn't (at > least for fdr) as > the NAs are ordered below the minimum p-value from > your vector in the > calculation. So if you fdr correct with the NAs > present then you get > more significant p-values than you should and the > results are > meaningless - and there's no error message. > > Obviously, the nice work by the developers will > correct this. > > >>Wenbin Liu wnbnl at yahoo.com > >>Wed Mar 23 23:51:28 CET 2005 > >> > >>Dear list, > >> > >>I'm puzzled by the R function p.adjust with NA > values > >>in the first argument. The adjustment gives > different > >>result with and without the NAs. > > > >Please refer to the extensive recent discussion on > this topic on the > >R-devel mailing list. > > > >> The question then is, > >>which approach should one take: with or without > NAs in > >>the first argument? > > > >The limma package functions remove NAs before using > p.adjust(), and I > >believe this is virtually always correct in the > microarray context. > > > >Gordon > > > >>Thanks a lot! > >> > >>Wenbin > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor >
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