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

Gordon Smyth smyth at wehi.edu.au
Fri Mar 5 00:24:19 MET 2004


At 11:01 AM 4/03/2004, p hu wrote:
>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,adjust="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???

To add to Jean and Jim's suggestions, you can use classifyTestsP() instead 
of classifyTests() to select genes based on individual p-values.

Gordon



More information about the Bioconductor mailing list