[BioC] Changes in siggenes?

Holger Schwender holger.schw at gmx.de
Thu Jan 7 18:29:06 CET 2010


Hi Torbjörn,

because of a few complaints that sam has too many confusing arguments (even though it is said in the vignette that these arguments can be ignored), I have put them into a control function called samControl (similar to rpart.control in rpart, glm.control in glm, ...) and you now can specify delta and p0 and other stuff by using the argument control in sam. See the man page of sam.

So specifying control=samControl(delta=somevalue, p0=someothervalue) in sam should solve your problem.

Best,
Holger 


-------- Original-Nachricht --------
> Datum: Thu, 7 Jan 2010 17:12:16 +0100
> Von: "Torbjörn Klatt" <torbjoern.k at googlemail.com>
> An: bioconductor at stat.math.ethz.ch
> Betreff: [BioC] Changes in siggenes?

> Hello Bioconductor followers,
> 
> I'm quite new to R and Bioconductor and as a student in biomathematics and
> attending a paper of computational biology I'm asked to identify
> significantly 
> expressed genes by a SAM analysis. We are working on the raw data set
> provided 
> by Wang [1] at GEO [2] and try do reproduce their procedure and analysis
> for 
> practical training.
> 
> For our first attempts we worked on one of the university's computers
> running 
> MS Windows XP Professional 32bit with SP3 and R 2.9.2 (2009-08-24). By
> reading 
> the help file for the sam() command we experimented a little bit and used
> the 
> attributes "delta" and "p0" amongst others. It worked well and we were
> rather 
> satisfied with the results.
> 
> Afterwards I installed R and Bioconductor on my own computer at home
> running 
> openSUSE 11.2 (64bit) with kernel 2.6.31.5-0.1 and R 2.10.1 (2009-12-14)
> with 
> additional Bioconductor packages installed directly from the repository on
> 2010/01/05. I configured and compiled R by myself using gcc 4.4.1 [3] and
> it's 
> complementary f77 [4] with no additional parameters.
> 
> I tried to run the same script we wrote in the university's computers and
> it 
> broke with some error messages.
> One of the errors was caused by the rma() command. This one could be fixed
> by 
> my professor. It seemed that there have been some changes in the affy
> package. 
> The fixed command (see file sam_analysis.r further down) is working on the
> old 
> university computers as well.
> 
> But the sam() command still did not work with the parameters "delta" and
> "p0" 
> and I got a error message saying that there are "unused parameters
> 'delta', 
> 'p0'.
> Although we could find a way without using these I would like to know
> since 
> when and why these parameters are not longer supported by sam(). I could
> not 
> find a very detailed change log of the siggenes package except of this one
> (http://fgc.lsi.umich.edu/cgi-bin/blosxom.cgi/siggenes), so I'm writing
> this 
> email.
> 
> Cheers,
> Torbjoern Klatt
> 
> PS: If this email is getting through to the list, it seems not possible to
> send PGP-signed mails. Is that right?
> 
> 
> --- file: sam_analysis.r ---
> #################################################
> # R-Script
> # author: Torbjoern Klatt
> # subject: Bioinformatik
> # project: SAM analysis 
> # date created: 2010-01-05
> # date edited last: 2010-01-06
> #################################################
> 
> # set the working directory
> setwd("/home/myself/Documents/Wissen/Uni/rac/0910_ws/Bioinformatik/Praktikum/wd")
> 
> # load required libraries
> library(affy)           # for Affymetrix chips
> library(siggenes)       # identifying significant genes
> library(hgu133a2.db)    # to map the affy probe names to gene names
> library(hopach)         # clustering
> 
> # read data about the phenotype (here dasatinib sensitivity)
> cell.lines <- read.csv("sensitivity.csv",row.names=1,header=TRUE,sep=",")
> pheno <- as.data.frame(cell.lines[,2],row.names=row.names(cell.lines))
> names(pheno) <- c("sensitivity")
> 
> # read the cell files and assign phenotype information
> wangData <- ReadAffy(phenoData=pheno)
> 
> ## old version of previous line
> ### wangData <- ReadAffy()
> ### wangData at phenoData<-as(pheno, "AnnotatedDataFrame")
> 
> # background correction, generation of expression values and normalization
> wangExpr <- rma(wangData)
> 
> # look at the expression data
> sampleNames(wangExpr)
> featureNames(wangExpr)
> description(wangExpr)
> pData(phenoData(wangExpr))
> dim(exprs(wangExpr))
> head(exprs(wangExpr))
> 
> # here one should do some more quality control, but this is omitted for
> now
> 
> # add the analysis here
> # with a 'rand' value of '123' the p0 in the SAM analysis will be 0.5
> sam.out <- sam(exprs(wangExpr), pData(phenoData(wangExpr))[,1],
> method=d.stat, 
> B=500, rand=123)
> ## old version of previous line
> ### sam.out <- sam(exprs(wangExpr), pData(phenoData(wangExpr))[,1], 
> method=d.stat, delta=seq(from=1.0 to=2.0 by=0.1), p0=0.5,B=500)
> delta <- findDelta(sam.out,fdr=0.05)
> genes <- list.siggenes(sam.out,delta[1,1])
> --- END: file---
> 
> --- sessionInfo() on my linux machine ---
> R version 2.10.1 (2009-12-14)
> x86_64-unknown-linux-gnu
> 
> locale:
>  [1] LC_CTYPE=de_DE.UTF-8       LC_NUMERIC=C
>  [3] LC_TIME=de_DE.UTF-8        LC_COLLATE=de_DE.UTF-8
>  [5] LC_MONETARY=C              LC_MESSAGES=de_DE.UTF-8
>  [7] LC_PAPER=de_DE.UTF-8       LC_NAME=C
>  [9] LC_ADDRESS=C               LC_TELEPHONE=C
> [11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C
> 
> attached base packages:
> [1] splines   stats     graphics  grDevices utils     datasets  methods
> [8] base
> 
> other attached packages:
>  [1] hgu133a2cdf_2.5.0   hopach_2.6.0        cluster_1.12.1
>  [4] hgu133a2.db_2.3.5   org.Hs.eg.db_2.3.6  RSQLite_0.8-0
>  [7] DBI_0.2-5           AnnotationDbi_1.8.1 siggenes_1.20.0
> [10] multtest_2.2.0      affy_1.24.2         Biobase_2.6.1
> 
> loaded via a namespace (and not attached):
> [1] affyio_1.14.0        MASS_7.3-5           preprocessCore_1.8.0
> [4] survival_2.35-8      tools_2.10.1
> --- END: sessionInfo() ---
> 
> --- sessionInfo() on the WinXP machine ---
> R version 2.9.2 (2009-08-24) 
> i386-pc-mingw32 
> 
> locale:
> LC_COLLATE=German_Germany.1252;LC_CTYPE=German_Germany.1252;LC_MONETARY=German_Germany.1252;LC_NUMERIC=C;LC_TIME=German_Germany.1252
> 
> attached base packages:
> [1] splines   stats     graphics  grDevices utils     datasets  methods  
> [8] base     
> 
> other attached packages:
>  [1] hopach_2.6.0        cluster_1.12.0      hgu133a2.db_2.2.11 
>  [4] RSQLite_0.8-0       DBI_0.2-5           AnnotationDbi_1.6.1
>  [7] siggenes_1.18.0     multtest_2.2.0      affy_1.22.1        
> [10] Biobase_2.4.1      
> 
> loaded via a namespace (and not attached):
> [1] affyio_1.12.0        MASS_7.2-48          preprocessCore_1.6.0
> [4] survival_2.35-4
> --- END: sessionInfo()
> 
> --- references ---
> [1] Xi-De Wang, Karen Reeves, Feng R Luo, Li-An Xu, Francis Lee, Edwin
> Clark, 
> Fei Huang. (2007). Identification of candidate predictive and surrogate 
> molecular markers for dasatinib in prostate cancer: rationale for patient 
> selection and efficacy monitoring. Genome biology 8 (11) p. R255 
> http://www.ncbi.nlm.nih.gov/pubmed/18047674
> [2] http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE9633
> [3] extracted from config.log: gcc version 4.4.1 [gcc-4_4-branch revision 
> 150839] (SUSE Linux)
> [4] extracted from config.log: GNU Fortran (SUSE Linux) 4.4.1
> [gcc-4_4-branch 
> revision 150839]
> 
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