title: Basic approaches to gene expression analysis of stem cells by microarrays.
abstract: This chapter covers gene expression analysis by microarray to study and characterize stem cells. In a case-study scenario, we describe basic bioinformatic methodologies used to answer common questions in microarray experiments involving one or more stem cell populations. Service providers or departmental core labs usually carry out sample preparation, hybridization, and scanning of microarrays. Therefore, in this chapter, we focus on the state-of-the-art data analysis that avoids common pitfalls and introduces the reader to important controls that yield robust biologically relevant results. We describe evaluation of differentially expressed genes, clustering methods, gene-set enrichment analysis, and gene network discovery methods that can be used to formulate meaningful biological insights as well as suggest new wet lab experiments.
authors.affiliation: Graduate School AICES, RWTH Aachen University, Aachen, Germany.
authors.forename: Bernhard
authors.initials: B
authors.lastname: Schuldt
authors.forename: Qiong
authors.initials: Q
authors.lastname: Lin
authors.forename: Franz-Josef
authors.initials: FJ
authors.lastname: Müller
authors.forename: Jeanne
authors.initials: J
authors.lastname: Loring
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D025341:Principal Component Analysis; D013234:Stem Cells / Q000378:metabolism*