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. 2010 Oct 15;26(20):2637-8.
doi: 10.1093/bioinformatics/btq471. Epub 2010 Aug 26.

DCGL: an R package for identifying differentially coexpressed genes and links from gene expression microarray data

Bao-Hong Liu  1 , Hui Yu, Kang Tu, Chun Li, Yi-Xue Li, Yuan-Yuan Li
Affiliations

DCGL: an R package for identifying differentially coexpressed genes and links from gene expression microarray data

Bao-Hong Liu et al. Bioinformatics. .

Abstract

Summary: Gene coexpression analysis was developed to explore gene interconnection at the expression level from a systems perspective, and differential coexpression analysis (DCEA), which examines the change in gene expression correlation between two conditions, was accordingly designed as a complementary technique to traditional differential expression analysis (DEA). Since there is a shortage of DCEA tools, we implemented in an R package 'DCGL' five DCEA methods for identification of differentially coexpressed genes and differentially coexpressed links, including three currently popular methods and two novel algorithms described in a companion paper. DCGL can serve as an easy-to-use tool to facilitate differential coexpression analyses.

Contact: yyli@scbit.org and yxli@scbit.org

Supplementary information: Supplementary data are available at Bioinformatics online.

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Figures

Fig. 1.
Fig. 1.
DCGL design. Function names are shown in italic texts.
See this image and copyright information in PMC

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