title: High throughput screening of co-expressed gene pairs with controlled false discovery rate (FDR) and minimum acceptable strength (MAS).
abstract: Many exploratory microarray data analysis tools such as gene clustering and relevance networks rely on detecting pairwise gene co-expression. Traditional screening of pairwise co-expression either controls biological significance or statistical significance, but not both. The former approach does not provide stochastic error control, and the later approach screens many co-expressions with excessively low correlation. We have designed and implemented a statistically sound two-stage co-expression detection algorithm that controls both statistical significance (false discovery rate, FDR) and biological significance (minimum acceptable strength, MAS) of the discovered co-expressions. Based on estimation of pairwise gene correlation, the algorithm provides an initial co-expression discovery that controls only FDR, which is then followed by a second stage co-expression discovery which controls both FDR and MAS. It also computes and thresholds the set of FDR p-values for each correlation that satisfied the MAS criterion. Using simulated data, we validated asymptotic null distributions of the Pearson and Kendall correlation coefficients and the two-stage error-control procedure; we also compared our two-stage test procedure with another two-stage test procedure using the receiver operating characteristic (ROC) curve. We then used yeast galactose metabolism data to illustrate the advantage of our method for clustering genes and constructing a relevance network. The method has been implemented in an R package "GeneNT" that is freely available from the Comprehensive R Archive Network (CRAN): www.cran.r-project.org/.
authors.affiliation: Bioinformatics Program, University of Michigan, Ann Arbor, MI 48109, USA. zhud@umich.edu
authors.forename: Dongxiao
authors.initials: D
authors.lastname: Zhu
authors.forename: Alfred O
authors.initials: AO
authors.lastname: Hero
authors.forename: Zhaohui S
authors.initials: ZS
authors.lastname: Qin
authors.forename: Anand
authors.initials: A
authors.lastname: Swaroop
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods* / Q000706:statistics & numerical data; D016001:Confidence Intervals; D020869:Gene Expression Profiling / Q000379:methods / Q000706:statistics & numerical data; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis / Q000706:statistics & numerical data