[BioC] select top genes based on p-value in limma

[Jean Yee Hwa Yang]

Hi Arne,

You can change the argument sort.by to sort.by="p", to select and sort the
values by p-value.  By default it is set to "B" which is the lods score.

Cheers

Jean

On Thu, 4 Mar 2004 Arne.Muller at aventis.com wrote:

> Hello,
> 
> I'm converting the limma fit into a data frame:
> 
> ...
> > fit3 <- eBayes(fit2)
> > d <- data.frame(fit3$"p.value", fit3$'lods')
> > colnames(d) <- c('pv', 'fc')
> > d[1:5,]
>            pv        fc
> 1 0.002538643 -1.470819
> 2 0.802832281 -6.320708
> 3 0.545533328 -6.155623
> 4 0.688787086 -6.267272
> 5 0.312317306 -5.799080
> > 
> 
> then suppose gnames is a vector of gene names, I select all genes with a
> p-value from the eBayes calculation <= 0.05:
> 
> > mygenes <- gnames[which(d[,'pv'] <= 0.05)]
> 
> Actually I'm still exploring the limma package, and I'm not sure what
> topTable actually does - it doesn' seem to return the genes by ordered
> p-value.
> 
> 	regards,
> 
> 	Arne
> 
> --
> Arne Muller, Ph.D.
> Toxicogenomics, Aventis Pharma
> arne dot muller domain=aventis com
> 
> > -----Original Message-----
> > From: bioconductor-bounces at stat.math.ethz.ch
> > [mailto:bioconductor-bounces at stat.math.ethz.ch]On Behalf Of p hu
> > Sent: 04 March 2004 01:02
> > To: bioconductor at stat.math.ethz.ch
> > Subject: [BioC] select top genes based on p-value in limma
> > 
> > 
> > Hi all,
> >  
> > For example, I used 
> >  
> > clas<-classifyTests(fit,p.value=0.05)
> > mycount<-vennCounts(clas, include="both")
> >  
> > and found there are 99 differentially expressed genes for my 
> > first comparsion.
> >  
> > then I do:
> >  
> > toptable1<-topTable(fit,coef=1,number=99,genelist=genelist,adj
> > ust="fdr")
> >  
> > this is part of the results
> >           Name          M         t      P.Value           B
> > 6820    H25306  2.9578622 21.779101 6.712472e-22 39.07274570
> > 6222    H25611  3.8097340 20.616434 3.472310e-21 37.73887184
> > 4394    H12333  2.9868665 13.285336 1.033728e-13 25.92910739
> > 2269    R31747  3.9112632 12.339976 1.164282e-12 23.86703473
> > 9171    R31507  3.7780976 11.834938 4.149866e-12 22.70578573
> > 11306 AA043477  1.6451826  9.087753 2.067361e-08 15.64724863
> > 596     H83378  1.1806774  7.498940 3.972530e-06 11.03899927
> > 9544    H42051  1.5306360  7.202912 9.726446e-06 10.14827317
> > 11320 AA054300  0.9058530  6.899348 2.492575e-05  9.22757718
> > 10132 AA135957  0.8268765  6.552645 7.535515e-05  8.16932543
> > 17941 AA149043  1.2592684  6.404648 1.149187e-04  7.71612881
> > 13461 AA211825  0.7310730  6.082586 3.242677e-04  6.72862309
> > ............................................................
> > 16930   W32999 -0.3562904 -2.861632 3.849730e-01 -2.36371124
> > 17667   W67427  0.4080262  2.859229 3.862250e-01 -2.36921005
> > 7769    H53894 -0.3463782 -2.856329 3.879989e-01 -2.37584026
> > 9751    W92088 -0.3139404 -2.854464 3.887059e-01 -2.38010239
> > 5067    H57545  0.8197179  2.851609 3.902150e-01 -2.38662381
> > 9468    R27989  0.3628438  2.848099 3.902150e-01 -2.39463557
> >  
> > As I can see here, the last gene has very high p-value 
> > although it is called DE gene.
> >  
> > So I am wondering how I can select genes based on a cut off 
> > p-value rather than a number that indicates how many genes I 
> > want to pick???
> >  
> > Thanks
> > 
> > 
> > 
> > 
> > ---------------------------------
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