title: DCGL: an R package for identifying differentially coexpressed genes and links from gene expression microarray data.
abstract: CONCLUSIONS
  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.
  
  
  BACKGROUND
  yyli@scbit.org and yxli@scbit.org
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: School of Life Science and Technology, Tongji University, Shanghai 200092, P R China.
authors.forename: Bao-Hong
authors.initials: BH
authors.lastname: Liu
authors.forename: Hui
authors.initials: H
authors.lastname: Yu
authors.forename: Kang
authors.initials: K
authors.lastname: Tu
authors.forename: Chun
authors.initials: C
authors.lastname: Li
authors.forename: Yi-Xue
authors.initials: YX
authors.lastname: Li
authors.forename: Yuan-Yuan
authors.initials: YY
authors.lastname: Li
mesh_terms: D000465:Algorithms; D030541:Databases, Genetic; D015870:Gene Expression; D020869:Gene Expression Profiling / Q000379:methods*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010363:Pattern Recognition, Automated; D012984:Software
references.citation: Bioinformatics. 2005 Dec 15;21(24):4348-55
references.pmid: 16234317
references.citation: Bioinformatics. 2006 Oct 1;22(19):2396-404
references.pmid: 16864591
references.citation: Endocrinology. 2009 Mar;150(3):1235-49
references.pmid: 18974276
references.citation: BMC Genomics. 2009 Jul 20;10:327
references.pmid: 19619308