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

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


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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Databases, Genetic
  • Gene Expression Profiling / methods*
  • Gene Expression*
  • Oligonucleotide Array Sequence Analysis / methods*
  • Pattern Recognition, Automated
  • Software*