title: Gene coexpression network analysis for family studies based on a meta-analytic approach.
abstract: For a better understanding of the biological mechanisms involved in complex traits or diseases, networks are often useful tools in genetic studies: coexpression networks based on pairwise correlations between genes are commonly used. In case of a family-based design, it can be problematic when there is a large between-family variation in expression levels. We propose here a gene coexpression network analysis for family studies. We build a coexpression network for each family and then combine the results. We applied our approach to data provided for analysis in the Genetic Analysis Workshop 19 and compared it to 2 naïve approaches-ignoring correlations among the expressions and decorrelating the gene expression by using the residuals of a mixed model-and a single-probe analysis. Our approach seemed to better deal with heterogeneity with regard to the naïve approaches. The naïve approaches did not provide any significant results, while our approach detected genes via indirect effects. It also detected more genes than the single-probe analysis.
authors.affiliation: Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands.
authors.forename: Renaud
authors.initials: R
authors.lastname: Tissier
authors.affiliation: Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands.
authors.forename: Hae-Won
authors.initials: HW
authors.lastname: Uh
authors.affiliation: Molecular epidemiology, Leiden University Medical Centre, Leiden, The Netherlands ; Pattern Recognition & Bioinformatics, Delft University of Technology, Leiden, The Netherlands.
authors.forename: Erik
authors.initials: E
authors.lastname: van den Akker
authors.affiliation: Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands.
authors.forename: Brunilda
authors.initials: B
authors.lastname: Balliu
authors.affiliation: Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands.
authors.forename: Spyridoula
authors.initials: S
authors.lastname: Tsonaka
authors.affiliation: Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands ; Department of Statistics, University of Leeds, Leeds, UK.
authors.forename: Jeanine
authors.initials: J
authors.lastname: Houwing-Duistermaat