Comparing statistical methods for constructing large scale gene networks

Jeffrey D. Allen, Yang Xie, Min Chen, Luc Girard, Guanghua Xiao

Research output: Contribution to journalArticle

112 Citations (Scopus)

Abstract

The gene regulatory network (GRN) reveals the regulatory relationships among genes and can provide a systematic understanding of molecular mechanisms underlying biological processes. The importance of computer simulations in understanding cellular processes is now widely accepted; a variety of algorithms have been developed to study these biological networks. The goal of this study is to provide a comprehensive evaluation and a practical guide to aid in choosing statistical methods for constructing large scale GRNs. Using both simulation studies and a real application in E. coli data, we compare different methods in terms of sensitivity and specificity in identifying the true connections and the hub genes, the ease of use, and computational speed. Our results show that these algorithms performed reasonably well, and each method has its own advantages: (1) GeneNet, WGCNA (Weighted Correlation Network Analysis), and ARACNE (Algorithm for the Reconstruction of Accurate Cellular Networks) performed well in constructing the global network structure; (2) GeneNet and SPACE (Sparse PArtial Correlation Estimation) performed well in identifying a few connections with high specificity.

Original languageEnglish (US)
Article numbere29348
JournalPLoS One
Volume7
Issue number1
DOIs
StatePublished - Jan 17 2012

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Gene Regulatory Networks
Statistical methods
statistical analysis
Genes
Biological Phenomena
molecular systematics
Electric network analysis
computer simulation
Computer Simulation
Escherichia coli
genes
Sensitivity and Specificity
Computer simulation
methodology
gene regulatory networks

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Comparing statistical methods for constructing large scale gene networks. / Allen, Jeffrey D.; Xie, Yang; Chen, Min; Girard, Luc; Xiao, Guanghua.

In: PLoS One, Vol. 7, No. 1, e29348, 17.01.2012.

Research output: Contribution to journalArticle

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