title: Improving identification of differentially expressed genes by integrative analysis of Affymetrix and Illumina arrays.
abstract: Together with the widely used Affymetrix microarrays, the recently introduced Illumina platform has become a cost-effective alternative for genome-wide studies. To efficiently use data from both array platforms, there is a pressing need for methods that allow systematic integration of multiple datasets, especially when the number of samples is small. To address these needs, we introduce a meta-analytic procedure for combining Affymetrix and Illumina data in the context of detecting differentially expressed genes between the platforms. We first investigate the effect of different expression change estimation procedures within the platforms on the agreement of the most differentially expressed genes. Using the best estimation methods, we then show the benefits of the integrative analysis in producing reproducible results across bootstrap samples. In particular, we demonstrate its biological relevance in identifying small but consistent changes during T helper 2 cell differentiation.
authors.affiliation: Department of Mathematics, University of Turku, Turku, Finland. laliel@utu.fi
authors.forename: Laura L
authors.initials: LL
authors.lastname: Elo
authors.forename: Mikko
authors.initials: M
authors.lastname: Katajamaa
authors.forename: Riikka
authors.initials: R
authors.lastname: Lund
authors.forename: Matej
authors.initials: M
authors.lastname: Oresic
authors.forename: Riitta
authors.initials: R
authors.lastname: Lahesmaa
authors.forename: Tero
authors.initials: T
authors.lastname: Aittokallio
mesh_terms: D002454:Cell Differentiation / Q000235:genetics; D002478:Cells, Cultured; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D018418:Th2 Cells / Q000166:cytology / Q000378:metabolism