Section: Computational Methods for High Throughput Genetic Analysis- Expression profiling Article: Differential Expression with the Bioconductor Project

A basic, yet challenging task in the analysis of microarray gene ex-pression data is the identification of changes in gene expression that are associated with particular biological conditions. We discuss different ap-proaches to this task and illustrate how they can be applied using software from the Bioconductor Project. A central problem is the high dimension-ality of gene expression space, which prohibits a comprehensive statistical analysis without focusing on particular aspects of the joint distribution of the genes ’ expression levels. Possible strategies are to do univariate gene–by–gene analysis, and to perform data–driven nonspecific filtering of genes before the actual statistical analysis. However, more focused strategies that make use of biologically relevant knowledge are more likely to increase our understanding of the data