title: Gene Set/Pathway enrichment analysis.
abstract: Thanks for the dramatic reduction of the costs of high-throughput techniques in modern biotechnology, searching for differentially expressed genes is already a common procedure in identifying biomarkers or signatures of phenotypic states such as diseases or compound treatments. However, in most of the cases, especially in complex diseases, even given a list of biomarkers, the underlying biological mechanisms are still obscure to us. In other words, rather than knowing what genes are involved, we are more interested in discovering the common, collective roles of all these genes. Based on the assumption that genes involved in the same biological processes, functions, or localizations present correlated behaviors in terms of expression levels, signal intensities, allele occurrences, and so on, we can therefore apply statistical tests to find perturbed pathways. Gene Set/Pathway enrichment analysis is one of such techniques; a step-by-step instruction is described in this chapter.
authors.affiliation: Program in Bioinformatics and Integrative Biology, Worcester, MA, USA. juihunghung@gmail.com
authors.forename: Jui-Hung
authors.initials: JH
authors.lastname: Hung
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000175:diagnosis / Q000235:genetics; D002874:Chromosome Mapping; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation; D006801:Humans; D015398:Signal Transduction