title: Identification of differentially expressed genes in microarray data in a principal component space.
abstract: Microarray experiments are often conducted in order to compare gene expression between two conditions. Tests to detected mean differential expression of genes between conditions are conducted applying correction for multiple testing. Seldom, relationships between gene expression and microarray conditions are investigated in a multivariate approach. Here we propose determining the relationship between genes and conditions using a Principal Component Analysis (PCA) space and classifying genes to one of two biological conditions based on their position relative to a direction on the PC space representing each condition.
authors.affiliation: Departamento de Estadística, Universidad Nacional de Colombia, Ciudad Universitaria carrera 30 con calle 45, edificio 404, Bogotá, Colombia.
authors.forename: Luis
authors.initials: L
authors.lastname: Ospina
authors.forename: Liliana
authors.initials: L
authors.lastname: López-Kleine
keywords: Cd closeness measure; Differentially expressed genes; Microarray data; Principal component analysis
references.citation: BMC Genet. 2010 Oct 15;11:94
references.pmid: 20950446
references.citation: J Bioinform Comput Biol. 2010 Dec;8(6):945-65
references.pmid: 21121020
references.citation: Appl Microbiol Biotechnol. 2012 Mar;93(5):2091-8
references.pmid: 22307501