Changes in siggenes?
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@torbjorn-klatt-3877
Last seen 9.6 years ago
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/Pra ktikum/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_MONETAR Y=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]
Prostate hgu133a2 probe affy siggenes ASSIGN Prostate hgu133a2 probe affy siggenes • 1.2k views
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@holger-schwender-344
Last seen 9.7 years ago
Hi Torbj?rn, 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: "Torbj?rn 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/P raktikum/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_MONET ARY=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] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor -- Jetzt kostenlos herunterladen: Internet Explorer 8 und Mozilla Firefox 3.5 - sicherer, schneller und einfacher! http://portal.gmx.net/de/go/atbrowser
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