[BioC] SAM analysis : samr package vs siggenes package

Cécile Laurent cecile.laurent at curie.fr
Tue Apr 22 15:22:14 CEST 2008


Hi Holger,

Thanks for your reply.
samr package is available in CRAN, developped by R. Tibshirani, G. Chu, 
T. Hastie, Balasubramanian Narasimhan and maintained by R. Tibshirani 
(so it does the same things as the Excel SAM, I think).

Actually, when I change the parameters, the results are almost but not 
exactly the same and I don't understand why.
For a same delta, FDR and false positive genes are slightly different. 
Can you explain me why ??

I also have a last question : why default parameters of these 2 packages 
are different?
Indeed, I don't know which parameters I have to choose and why?

Regards,
Cecile



Holger Schwender a écrit :
> Hi Cecile,
>
> I do not know the samr package. But if it does the same things as the Excel SAM has done a few years ago, then you should set var.equal=TRUE, med=TRUE and lambda=0.5(??) in the siggenes SAM. The latter should lead to the same estimation of pi0. Moreover, you need to use the same permutations of the class labels. If you can get these permutations from samr, you will be able to use in these permutations in sam by specifying mat.samp. 
>
> Best,
> Holger
>
>
> -------- Original-Nachricht --------
>   
>> Datum: Mon, 21 Apr 2008 14:54:48 +0200
>> Von: "Cécile Laurent" <cecile.laurent at curie.fr>
>> An: bioconductor at stat.math.ethz.ch
>> Betreff: [BioC] SAM analysis : samr package vs siggenes package
>>     
>
>   
>> Hi,
>>
>> I would like to know why when I run SAM analysis with SamR and Siggenes 
>> packages, I don't have the same results for the small pvalues.
>> I test here on golub data, and I don't have the same differential genes 
>> number when I observe the delta tables (delta.table for samr and 
>> sam.out at mat.fdr for siggenes) for a FDR 0% (250 are differential with 
>> samr package and 9 with siggenes package).
>> On my personnal data, I observe the same difference in differential gene 
>> number at FDR 5%.
>> I also observe the same s0, but not the same pi0, in the 2 sam objects.
>> I think, in my code, the parameters are the same... So, I don't know 
>> which package used...
>> Is it something wrong???
>> Can you explain me these differences in the results..
>>
>> Thanks,
>> Cécile
>>
>>
>> Here is my sessionInfo()
>>
>> R version 2.6.0 (2007-10-03)
>> i486-pc-linux-gnu
>>
>> locale:
>> LC_CTYPE=fr_FR.UTF-8;LC_NUMERIC=C;LC_TIME=fr_FR.UTF-8;LC_COLLATE=fr_FR.UTF-8;LC_MONETARY=fr_FR.UTF-8;LC_MESSAGES=fr_FR.UTF-8;LC_PAPER=fr_FR.UTF-8;LC_NAME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=fr_FR.UTF-8;LC_IDENTIFICATION=C
>>
>> attached base packages:
>> [1] splines   tools     stats     graphics  grDevices utils     datasets
>> [8] methods   base    
>>
>> other attached packages:
>> [1] siggenes_1.12.0 samr_1.25       impute_1.0-5    multtest_1.18.0
>> [5] survival_2.33   Biobase_1.16.0
>>
>> loaded via a namespace (and not attached):
>> [1] rcompgen_0.1-15
>>
>>
>> ### My code :
>> library(multtest)
>> library(samr)
>> library(siggenes)
>> data(golub)
>> golubCl=golub.cl
>> golubCl[which(golub.cl==1)]=2
>> golubCl[which(golub.cl==0)]=1
>>
>> ## SamR package
>> samrData=list(x=golub, y=golubCl, geneid=golub.gnames[,3], 
>> genesnames=golub.gnames[,3], logged2=T)
>> samr.obj=samr(samrData, resp.type="Two class unpaired", 
>> testStatistic="standard", nperms=1000, random.seed=123)
>> delta.table=samr.compute.delta.table(samr.obj, dels=seq(0.1,5,0.05))
>> pv.samr=samr.pvalues.from.perms(samr.obj$tt, samr.obj$ttstar)
>>
>> ## Siggenes package
>> sam.out=sam(golub, golub.cl, rand=123,B=1000, 
>> gene.names=golub.gnames[,3], method="d.stat", var.equal=T, s0=NA, 
>> include.zero=F, delta=seq(0.1,5,0.05) )
>>
>> ## plot to observe the values (the version with -log() to see the 
>> difference in the small pvalues)
>> #plot(sam.out at d[order(sam.out at d)],samr.obj$tt[order(samr.obj$tt)])
>> #plot(-log(sam.out at d[order(sam.out at d)]),-log(samr.obj$tt[order(samr.obj$tt)]))
>> plot(sam.out at p.value[order(sam.out at p.value)],pv.samr[order(pv.samr)])
>> plot(-log(sam.out at p.value[order(sam.out at p.value)]),-log(pv.samr[order(pv.samr)]))
>>
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>
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