## ----label='version', include=FALSE, cache=FALSE------------------------------ #suppressPackageStartupMessages(library(Biobase)) library(Biobase) pkg.ver <- package.version("hgu133plus2CellScore") ## ----label='Setup', include=FALSE, cache=FALSE---------------------- ## Save the current working directory dir.main <- getwd() ## Set the name of the directory in which figures will be saved (if any) dir.figures <- 'figures' ## global chunk options library(knitr) opts_chunk$set( concordance=FALSE, cashe=2, ## cache is only valid with a specific version of R and session info ## cache will be kept for at most a month (re-compute the next month) cache.extra=list(R.version, sessionInfo(), format(Sys.Date(), '%Y-%m') ), autodep=TRUE, fig.path=paste0(dir.figures,"/"), tidy=FALSE, size="small", message=FALSE, warning=FALSE ) options(width=70, promp="R> ", continue="+ ", useFancyQuotes=FALSE) ## ----eval=FALSE----------------------------------------------------- # if (!requireNamespace("BiocManager", quietly=TRUE)) # install.packages("BiocManager") # BiocManager::install() ## ----eval=FALSE----------------------------------------------------- # BiocManager::install("hgu133plus2CellScore") ## ----eval=TRUE, echo=FALSE, cache=FALSE----------------------------- options(BIOCINSTALLER_ONLINE_DCF=FALSE) ## ----eval=TRUE, echo=1:2, cache=FALSE, include=TRUE----------------- library(Biobase) library(hgu133plus2CellScore) ## ----eval=TRUE------------------------------------------------------ eset.std ## ----eval=FALSE----------------------------------------------------- # ## Install affy # if (!requireNamespace("BiocManager", quietly=TRUE)) # install.packages("BiocManager") # BiocManager::install("affy") # ## Install YuGene # install.packages("YuGene") # # ## Load the packages # library(affy) # library(YuGene) # # ## Read in all *.CEL files in the current working directory; # ## if the files are not in the working directory then uncomment # ## the first command line and then read the files. Note that # ## path_to_CEL should be replaced with path to the directory # ## containing the *.CEL files # # #setwd(path_to_CEL) # data <- ReadAffy() # # ## Background noise correction # bg.corr <- expresso(data, bg.correct=TRUE, bgcorrect.method="rma", # normalize=FALSE, pmcorrect.method="pmonly", # summary.method="avgdiff") # ## Log2-transform the background corrected data # bg.corr.log2 <- log2(bg.corr) # ## Perform YuGene transform (that results with # ## normalized expression values between 0 and 1) # normalized.matrix <- YuGene(bg.corr.log2) # # ## Calculate mas5 present/absent calls # co <- mas5calls(data) # co <- assayData(co)[["se.exprs"]] #extract detection p-values # pvalue.detection.cutoff <- 0.05 # calls.matrix <- co < pvalue.detection.cutoff ## ----eval=FALSE----------------------------------------------------- # ## Example code: # ## Create a new assayData object from the normalized expression data # ## and the calls matrix # assay.data <- assayDataNew(exprs=as.matrix(normalizedSub.matrix), # calls=as.matrix(callsSub.matrix) ) # ## Create an AnnotatedDataFrame object from the phenotype data frame # pheno.table <- new("AnnotatedDataFrame", data=phenotype.data.frame) # ## Create an AnnotatedDataFrame object from the annotation data frame # annotation.table <- new("AnnotatedDataFrame", data=annotation.data.frame) # ## Create the new ExpressionSet object with all the data in one object # eset.std <- ExpressionSet(assayData=assay.data, # phenoData=pheno.table, # featureData=annotation.table) ## ----eval=TRUE, echo=TRUE------------------------------------------- sessionInfo()