R version 2.10.1 (2009-12-14) Copyright (C) 2009 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. Natural language support but running in an English locale R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > library(affycompData, lib.loc="/home/hjaffee/Rlibs+") Loading required package: Biobase Welcome to Bioconductor Vignettes contain introductory material. To view, type 'openVignette()'. To cite Bioconductor, see 'citation("Biobase")' and for packages 'citation(pkgname)'. > library(affycomp, lib.loc="/home/hjaffee/Rlibs+") > > library(tools) > # library(modreg) -- now in stats > > dilution.ngenes <- 0 > spikein.ngenes <- 0 > spikein133.ngenes <- 0 > ###read in nickname and other info > affycomp.info <- read.table("info.txt",sep="\t",as.is=TRUE,quote="") > method.name <- affycomp.info[3,2] > verbose <- TRUE > > # Read in the 3 files and perform assessments (if files exist). > > # HJ Feb 23, 2010 > ## make/save assessments (used to be in save_assessments.R) > > dir.create("data") > f <- "dilution.csv" > if(file.exists(f)){ + d <- read.dilution(f) + if(verbose) cat("Performing 3 assessments on dilution data...") + dilution.assessment <- assessDilution(d,method.name=method.name) + save(dilution.assessment,file="data/dilution.assessment.rda",compress=TRUE) + # added by HJ - Jan 13, 04 + tmp.assessment <- c(Dilution=list(dilution.assessment)) + if(verbose) cat("\n") + dilution.ngenes <- nrow(exprs(d)) + } Performing 3 assessments on dilution data... > > f <- "hgu95.csv" > if(file.exists(f)){ + s <- read.spikein(f,"hgu95a") + spikein.assessment <- + assessSpikeIn(s,verbose=verbose,method.name=method.name) + save(spikein.assessment,file="data/spikein.assessment.rda",compress=TRUE) + if(exists("dilution.assessment")){ + tmp.assessment <- c(Dilution=list(dilution.assessment),spikein.assessment) + tmp.assessment["what"] <- "All" + } + spikein.assessment2 <- + assessSpikeIn2(s,verbose=verbose,method.name=method.name) + save(spikein.assessment2,file="data/spikein.assessment2.rda",compress=TRUE) + spikein.ngenes <- nrow(exprs(s)) + } Performing 6 assessments that will take a few minutes...... Using only a subset of the spike in data Performing 3 assessments that will take a few seconds... > > f <- "hgu133.csv" > if(file.exists(f)){ + s <- read.spikein(f,"hgu133a") + spikein.assessment.133 <- + assessSpikeIn(s,verbose=verbose,method.name=method.name) + save(spikein.assessment.133,file="data/spikein.assessment.133.rda",compress=TRUE) + spikein.assessment2.133 <- + assessSpikeIn2(s,verbose=verbose,method.name=method.name) + save(spikein.assessment2.133,file="data/spikein.assessment2.133.rda",compress=TRUE) + spikein133.ngenes <- nrow(exprs(s)) + } > ## end of make/save assessments > > # Now, if correct assessment lists exist we run Sweave and make tables. > dir <- paste(.path.package("affycomp"),"Rnw",sep="/") > > F1 <- exists("dilution.assessment") > F2 <- exists("spikein.assessment") > F3 <- exists("spikein.assessment.133") > > Table <- matrix(NA,23,1) > > if(F1 & F2){ + Table <- tableAll(tmp.assessment) + + Table2 <- rbind(tableAll(spikein.assessment), + tableAll(spikein.assessment2)) + + results2 <- "results2.txt" + Table2 <- rbind(Table2,spikein.ngenes) + write(Table2,file=results2,ncol=1) + + Sweave(paste(dir,"comparison.Rnw",sep="/")) + Sweave(paste(dir,"simple.Rnw",sep="/")) + Sweave(paste(dir,"complete-assessment.Rnw",sep="/")) + } Writing to file comparison.tex Processing code chunks ... 1 : term hide 2 : term verbatim 3 : term verbatim 4 : term verbatim eps pdf 5 : term verbatim eps pdf 6 : term verbatim eps pdf 7 : term verbatim eps pdf 8 : term verbatim eps pdf 9 : term verbatim eps pdf 10 : term verbatim eps pdf 11 : term verbatim eps pdf 12 : term verbatim eps pdf 13 : term verbatim eps pdf 14 : term verbatim eps pdf 15 : term verbatim eps pdf You can now run LaTeX on 'comparison.tex' Writing to file simple.tex Processing code chunks ... 1 : term hide 2 : term verbatim 3 : echo term verbatim 4 : term verbatim eps pdf 5 : term verbatim eps pdf 6 : term verbatim eps pdf 7 : term verbatim eps pdf 8 : term verbatim eps pdf 9 : term verbatim eps pdf 10 : term verbatim eps pdf 11 : term verbatim eps pdf 12 : term verbatim eps pdf You can now run LaTeX on 'simple.tex' Writing to file complete-assessment.tex Processing code chunks ... 1 : term hide 2 : term verbatim 3 : term verbatim 4 : term verbatim 5 : term verbatim eps pdf 6 : term verbatim eps pdf 7 : term verbatim eps pdf 8 : term verbatim eps pdf 9 : term verbatim eps pdf 10 : term verbatim eps pdf 11 : term verbatim eps pdf 12 : term verbatim eps pdf 13 : term verbatim eps pdf 14 : term verbatim eps pdf 15 : term verbatim eps pdf 16 : term verbatim eps pdf 17 : term verbatim eps pdf 18 : term verbatim eps pdf 19 : term verbatim eps pdf You can now run LaTeX on 'complete-assessment.tex' > > if(F1 & !F2){ + Table[1:6,] <- tableAll(dilution.assessment) + + Sweave(paste(dir,"dilution-assessment.Rnw",sep="/")) + } > > if(!F1 & F2){ + Table[7:23,] <- tableAll(spikein.assessment) + Table2 <- rbind(tableAll(spikein.assessment), + tableAll(spikein.assessment2)) + + results2 <- "results2.txt" + Table2 <- rbind(Table2,spikein.ngenes) + write(Table2,file=results2,ncol=1) + + Sweave(paste(dir,"spike-in-assessment.Rnw",sep="/")) + } > > if(F3){ + Table2.133 <- rbind(tableAll(spikein.assessment.133), + tableAll(spikein.assessment2.133)) + + results2.133 <- "results2-133.txt" + Table2.133 <- rbind(Table2.133,spikein133.ngenes) + write(Table2.133,file=results2.133,ncol=1) + Sweave(paste(dir,"spike-in-133-assessment.Rnw",sep="/")) + } > if(F1 | F2){ + Table <- rbind(Table,spikein.ngenes,dilution.ngenes) + results <- "results.txt" + write(Table,file=results,ncol=1) + } > > proc.time() user system elapsed 36.707 0.371 37.140