title: Moderated effect size and P-value combinations for microarray meta-analyses.
abstract: BACKGROUND
  With the proliferation of microarray experiments and their availability in the public domain, the use of meta-analysis methods to combine results from different studies increases. In microarray experiments, where the sample size is often limited, meta-analysis offers the possibility to considerably increase the statistical power and give more accurate results.
  
  
  RESULTS
  A moderated effect size combination method was proposed and compared with other meta-analysis approaches. All methods were applied to real publicly available datasets on prostate cancer, and were compared in an extensive simulation study for various amounts of inter-study variability. Although the proposed moderated effect size combination improved already existing effect size approaches, the P-value combination was found to provide a better sensitivity and a better gene ranking than the other meta-analysis methods, while effect size methods were more conservative.
  
  
  BACKGROUND
  An R package metaMA is available on the CRAN.
authors.affiliation: INRA, UMR 1313 Génétique Animale et Biologie Intégrative, Jouy-en-Josas, F-78350, France. guillemette.marot@jouy.inra.fr
authors.forename: Guillemette
authors.initials: G
authors.lastname: Marot
authors.forename: Jean-Louis
authors.initials: JL
authors.lastname: Foulley
authors.forename: Claus-Dieter
authors.initials: CD
authors.lastname: Mayer
authors.forename: Florence
authors.initials: F
authors.lastname: Jaffrézic
mesh_terms: D000818:Animals; D003198:Computer Simulation; D020869:Gene Expression Profiling / Q000379:methods; D006801:Humans; D008297:Male; D015201:Meta-Analysis as Topic; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D011471:Prostatic Neoplasms / Q000235:genetics / Q000378:metabolism