\name{plotGeneWiseBoxPlot} \alias{plotGeneWiseBoxPlot} \title{Create gene-wise boxplot from (merged) ExpressionSet} \description{Gene-wise boxplots describe the gene-wise distribution of samples. Sample can be grouped together using the batchLabel parameter and can be coloroed usig the colLabel parameter for optimal visualization of the possible batch effects.} \usage{ plotGeneWiseBoxPlot(eset, colLabel, batchLabel, gene=NULL, legend=TRUE, file=NULL, ...) } \arguments{ \item{eset}{ExpressionSet object.} \item{colLabel}{colname in pData(eset) to retrieve information for the labeling of samples with a color. All samples with the same value in pData(eset)[,colLabel] will share the same color.} \item{batchLabel}{colname in pData(eset) to retrieve information for the grouping of samples. All samples with the same value in pData(eset)[,batchLabel] and with the same color will be grouped together.} \item{gene}{Gene for which the boxplot will be created. If not specified a random gene will be selected.} \item{legend}{If TRUE a legend will be provided next to the gene-wise box plot.} \item{file}{If defined, the resulting plot will be stored as a pdf file instead of shown interactively.} \item{...}{Additional parameters for the 'plot' function (e.g. 'main').} } \examples{ # retrieve two datasets: library(inSilicoDb); eset1 = getDataset("GSE19804", "GPL570", norm="FRMA", genes=TRUE); eset2 = getDataset("GSE10072", "GPL96", norm="FRMA", genes=TRUE); esets = list(eset1,eset2); # merge them using the 'NONE' and 'COMBAT' method: library(inSilicoMerging) eset_NONE = merge(esets, method="NONE"); eset_COMBAT = merge(esets, method="COMBAT"); # check available annotations: colnames(pData(eset_NONE)) table(pData(eset_NONE)[,"Disease"]); table(pData(eset_NONE)[,"Study"]); # Visual inspection of a random gene in the two merged datasets gene = sample(rownames(exprs(eset_NONE)), 1) plotGeneWiseBoxPlot(eset_NONE, colLabel="Disease", batchLabel="Study", gene=gene) plotGeneWiseBoxPlot(eset_COMBAT, colLabel="Disease", batchLabel="Study", gene=gene) }