title: A rapid method for microarray cross platform comparisons using gene expression signatures.
abstract: Microarray technology has become highly valuable for identifying complex changes in global gene expression patterns. The inevitable use of a variety of different platforms has compounded the difficulty of effectively comparing data between projects, laboratories, and public access databases. The need for consistent, believable results across platforms is fundamental and methods for comparing results across platforms should be as straightforward as possible. We present the results of a study comparing three major, commercially available, microarray platforms (Affymetrix, Agilent, and Illumina). Concordance estimates between platforms was based on mapping of probes to Human Gene Organization (HUGO) gene names. Appropriate data normalization procedures were applied to each dataset followed by the generation of lists of regulated genes using a common significance threshold for all three platforms. As expected, concordance measured by directly comparing gene lists was relatively low (an average 22.8% for all platforms across all possible comparisons). However, when statistical tests (gene set enrichment analysis--GSEA, parametric analysis of gene enrichment--PAGE) which align gene lists with continuous measures of differential gene expression were applied to the cross platform datasets using significant gene lists to poll entire datasets, the relatedness of the results from all three platforms was specific, obvious, and profound.
authors.affiliation: Genomics Core, Division of Allergy and Clinical Immunology, School of Medicine, Johns Hopkins University, Mason Lord Bldg., Center Tower, Rm. 664, 5200 Eastern Avenue, Baltimore, MD 21224, USA. ccheadl1@jhmi.edu
authors.forename: Chris
authors.initials: C
authors.lastname: Cheadle
authors.forename: Kevin G
authors.initials: KG
authors.lastname: Becker
authors.forename: Yoon S
authors.initials: YS
authors.lastname: Cho-Chung
authors.forename: Maria
authors.initials: M
authors.lastname: Nesterova
authors.forename: Tonya
authors.initials: T
authors.lastname: Watkins
authors.forename: William
authors.initials: W
authors.lastname: Wood
authors.forename: Vinayakumar
authors.initials: V
authors.lastname: Prabhu
authors.forename: Kathleen C
authors.initials: KC
authors.lastname: Barnes
mesh_terms: D000818:Animals; D054757:Cyclic AMP-Dependent Protein Kinase RIIbeta Subunit; D054756:Cyclic AMP-Dependent Protein Kinase RIalpha Subunit; D017868:Cyclic AMP-Dependent Protein Kinases / Q000235:genetics; D015536:Down-Regulation; D020869:Gene Expression Profiling / Q000379:methods* / Q000592:standards; D015971:Gene Expression Regulation, Enzymologic; D052138:Genes, Neoplasm; D006801:Humans; D051379:Mice; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods* / Q000592:standards*; D015203:Reproducibility of Results; D013997:Time Factors; D015854:Up-Regulation
chemical_list: D054757:Cyclic AMP-Dependent Protein Kinase RIIbeta Subunit; D054756:Cyclic AMP-Dependent Protein Kinase RIalpha Subunit; C517834:PRKAR1A protein, human; C517837:PRKAR2B protein, human; C517835:Prkar1a protein, mouse; C517838:Prkar2b protein, mouse; D017868:Cyclic AMP-Dependent Protein Kinases