An integrated approach for the analysis of biological pathways using mixed models

Lily Wang, Bing Zhang, Russell D. Wolfinger, Xi Chen

Research output: Contribution to journalArticle

43 Citations (Scopus)

Abstract

Gene class, ontology, or pathway testing analysis has become increasingly popular in microarray data analysis. Such approaches allow the integration of gene annotation databases, such as Gene Ontology and KEGG Pathway, to formally test for subtle but coordinated changes at a system level. Higher power in gene class testing is gained by combining weak signals from a number of individual genes in each pathway. We propose an alternative approach for gene-class testing based on mixed models, a class of statistical models that: a) provides the ability to model and borrow strength across genes that are both up and down in a pathway, b) operates within a well-established statistical framework amenable to direct control of false positive or false discovery rates, c) exhibits improved power over widely used methods under normal location-based alternative hypotheses, and d) handles complex experimental designs for which permutation resampling is difficult. We compare the properties of this mixed models approach with nonparametric method GSEA and parametric method PAGE using a simulation study, and illustrate its application with a diabetes data set and a dose-response data set.

Original languageEnglish (US)
Article numbere1000115
JournalPLoS Genetics
Volume4
Issue number7
DOIs
StatePublished - Jul 1 2008
Externally publishedYes

Fingerprint

integrated approach
Gene Ontology
gene
Genes
genes
Molecular Sequence Annotation
Statistical Models
Microarray Analysis
testing
Research Design
Databases
statistical models
diabetes
dose response
analysis
data analysis
experimental design
methodology
Datasets
simulation

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Molecular Biology
  • Genetics
  • Genetics(clinical)
  • Cancer Research

Cite this

An integrated approach for the analysis of biological pathways using mixed models. / Wang, Lily; Zhang, Bing; Wolfinger, Russell D.; Chen, Xi.

In: PLoS Genetics, Vol. 4, No. 7, e1000115, 01.07.2008.

Research output: Contribution to journalArticle

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