[BioC] Inf values using SAM (package=siggenes)

[Holger Schwender]

Dear Julian,

the only values that are infinitive are the values of cutlow and cutup, where cutup is the smallest value of the test statistic for a gene to be called differentially expressed if its test value is larger than zero, and cutup is the largest test score less than zero for a gene to be called differentially expressed. If none of the genes is called differentially expressed by SAM than cutlow and cutup are set to -Inf and Inf, respectively. This has both practical and theoretical reasons.

Best,
Holger

-------- Original-Nachricht --------
> Datum: Fri, 28 Dec 2007 11:43:33 +0800 (SGT)
> Von: Julian Lee <julian at omniarray.com>
> An: bioconductor at stat.math.ethz.ch
> Betreff: [BioC] Inf values using SAM (package=siggenes)

> Dear All,
> 
> I'm having some problems trying to find differentially expressed genes
> using SAM. I have the SAM for excel version but that unfortunately is limited
> to only 500 genes.
> 
> >from the vignette, i'm supplying the sam function, two important
> arguments, data and cl.
> 
> > data
> ExpressionSet (storageMode: lockedEnvironment)
> assayData: 16304 features, 65 samples 
>   element names: exprs 
> phenoData
>   rowNames: D02_2nd, D02_3rd, ..., D31_BL (65 total)
>   varLabels and varMetadata:
>     Patient_ID: Patient's ID
>     Patient_Initials: Patient's Initials
>     ...: ...
>     25_at_cycle1: 25% reduction from baseline at cycle1
>     (17 total)
> featureData
>   rowNames: 1007_s_at, 1053_at, ..., AFFX-r2-Ec-bioD-5_at (16304 total)
>   varLabels and varMetadata: none
> experimentData: use 'experimentData(object)'
> Annotation [1] "hgu133plus2"
> 
> >cl
> [1] 1 1 0 1 1 0 1 1 0 1 0 1 1 1 1 1 0 1 1 0 1 1 0 1 1 0 1 1 0 1 1 1 0 1 1
> 0 1 1
> [39] 1 1 0 1 1 0 1 1 0 1 1 1 0 1 0 1 1 0 1 1 0 1 0 1 0 1 0
> 
> data was pre-processed using the rma function, followed by genefiltering
> 
> >data<-rma(U133PLUS2 CELFILES)
> >library(genefilter)
> >f1<-pOverA(0.25,log2(100))
> >f2<-function(x) (IQR(x)>0.5)
> >ff<-filterfun(f1,f2)
> >data<-data[genefilter(data,ff),]
> 
> ##56,000 genes reduced to 16304 genes
> 
> >library(siggenes)
> 
> >sam.out<-sam(exprs(data),cl,rand=1234)
> >sam.out
> SAM Analysis for the Two-Class Unpaired Case Assuming Unequal Variances 
>  
>    Delta p0 False Called FDR
> 1    0.1  1     0      0   0
> 2    0.2  1     0      0   0
> 3    0.3  1     0      0   0
> 4    0.4  1     0      0   0
> 5    0.5  1     0      0   0
> 6    0.6  1     0      0   0
> 7    0.7  1     0      0   0
> 8    0.8  1     0      0   0
> 9    0.9  1     0      0   0
> 10   1.0  1     0      0   0
> 
> >summary(sam.out)
> SAM Analysis for the Two-Class Unpaired Case Assuming Unequal Variances 
>  
>  s0 = 0.0735  (The 0 % quantile of the s values.) 
>  
>  Number of permutations: 100  
> 
>  MEAN number of falsely called variables is computed.
> 
>    Delta p0 False Called FDR cutlow cutup j2    j1
> 1    0.1  1     0      0   0   -Inf   Inf  0 16305
> 2    0.2  1     0      0   0   -Inf   Inf  0 16305
> 3    0.3  1     0      0   0   -Inf   Inf  0 16305
> 4    0.4  1     0      0   0   -Inf   Inf  0 16305
> 5    0.5  1     0      0   0   -Inf   Inf  0 16305
> 6    0.6  1     0      0   0   -Inf   Inf  0 16305
> 7    0.7  1     0      0   0   -Inf   Inf  0 16305
> 8    0.8  1     0      0   0   -Inf   Inf  0 16305
> 9    0.9  1     0      0   0   -Inf   Inf  0 16305
> 10   1.0  1     0      0   0   -Inf   Inf  0 16305
> 
> I'm not too sure why i'm getting Infinity values. This is my first time
> using SAM on bioconductor. 
> 
> Thank you
> 
> regards
> 
> Julian Lee
> National Cancer Center Singapore
> 
> >sessionInfo()
> R version 2.5.1 (2007-06-27) 
> i386-pc-mingw32 
> 
> locale:
> LC_COLLATE=English_United States.1252;LC_CTYPE=English_United
> States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United
> States.1252
> 
> attached base packages:
> [1] "splines"   "tools"     "stats"     "graphics"  "grDevices" "utils"   
> [7] "datasets"  "methods"   "base"     
> 
> other attached packages:
> genefilter       maDB      limma       affy     affyio   siggenes  
> multtest 
>   "1.14.1"    "1.8.0"   "2.10.5"   "1.14.2"    "1.4.1"   "1.10.1"  
> "1.16.1" 
>   survival    Biobase 
>     "2.32"   "1.14.1"
> 
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