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Hi Greg, Alvord, Greg (DMS) [Contr] wrote: > Dear List, > > > > I am a newcomer to R and an absolute rank rookie with > Bioconductor and microarray analysis. I am trying to find the gene > expression summary values in the Dilution data set. I am working > through the 2nd chapter of the book by Gentlemen, Carey, Huber, Irizarry > and Dudoit (BACBSURAB). My question is simple: Have I obtained the > matrix/data frame containing the summary expression values after > correcting for background (convolution method), normalizing (quantile > method) using the rma function? Many thanks. > > > > Here are the commands: > > > > >>library('affy') > > > Loading required package: Biobase > > Loading required package: tools > > > > Welcome to Bioconductor > > > > Vignettes contain introductory material. > > To view, simply type 'openVignette()' or start with > 'help(Biobase)'. > > For details on reading vignettes, see the openVignette help > page. > > > > >>library('affydata') > > >>data(Dilution) > > >>eset <- rma(Dilution) > > > Background correcting > > Normalizing > > Calculating Expression > > >>attributes.eset <- attributes(eset) > > >>names(attributes.eset) > > > [1] "exprs" "se.exprs" "description" "annotation" "notes" > > > [6] "reporterInfo" "phenoData" "class" > > >>eset.exprs <- attributes.eset$exprs > > >>eset.exprs.df <- data.frame(eset.exprs) > > >>dim(eset.exprs.df) > > > [1] 12625 4 > > >>summary(eset.exprs.df) > > > X20A X20B X10A X10B > > Min. : 2.266 Min. : 2.220 Min. : 2.239 Min. : 2.246 > > 1st Qu.: 4.725 1st Qu.: 4.689 1st Qu.: 4.727 1st Qu.: 4.697 > > Median : 6.229 Median : 6.210 Median : 6.233 Median : 6.215 > > Mean : 6.190 Mean : 6.178 Mean : 6.191 Mean : 6.183 > > 3rd Qu.: 7.519 3rd Qu.: 7.513 3rd Qu.: 7.514 3rd Qu.: 7.528 > > Max. :13.402 Max. :13.403 Max. :13.443 Max. :13.489 > > >>eset.exprs.df[1:3,] > > > X20A X20B X10A X10B > > 100_g_at 8.039951 7.891520 8.022282 7.910679 > > 1000_at 7.790855 7.661225 7.716811 7.622734 > > 1001_at 5.175568 5.067023 5.082672 5.091804 > > > > Is this data frame, eset.exprs.df, that contains the summary expression > values after correcting for background (convolution method), normalizing > (quantile method) using the rma function? Yes, but note that the canonical method to get these data is to use the exprs() accessor. In this case you would do: eset.exprs.df <- exprs(eset) by using the accessor functions you are protected from any underlying changes that may have been made to the package. HTH, Jim > > > > Thank you very much, > > > > Greg > > > > W. Gregory Alvord, Ph.D. > > Director, Statistical Consulting Services > > Computer and Statistical Services > > National Cancer Institute at Frederick > > Fort Detrick at 7th Street > > Post Office Box B > > Miller Drive, Building 362, Room 33 > > Frederick, MD 21702-1201 > > Phone: 301.846.5101 > > Fax: 301.846.6196 > > E-mail: gwa at css.ncifcrf.gov > > > > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor -- James W. MacDonald, M.S. Biostatistician Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623 ********************************************************** Electronic Mail is not secure, may not be read every day, and should not be used for urgent or sensitive issues.