CGGA

CGGA (Co-expressed Gene Groups Analysis)
Release date 2006
Implementation R
Authors Martinez, R., Pasquier, N., and Pasquier, C.
Availability binary downloadable here

CGGA (Co-expressed Gene Groups Analysis) (Martinez et al. 2008, Martinez2006; 2006a, 2006b) performs the extraction of bi-clusters of co-regulated genes from integrated gene expression data and gene annotations obtained from biological knowledge. First, the gene rank hierarchy is constructed using SAM F-Scores and then, the CGGA algorithm is applied to group of co-expressed genes.

Martinez, R., Pasquier, N., and Pasquier, C. (2008), “GenMiner: mining non-redundant association rules from integrated gene expression data and annotations.” Bioinformatics (Oxford, England), Oxford Academic, 24, 2643–4. https://doi.org/10.1093/bioinformatics/btn490.

Martinez, R., Pasquier, N., Collard, M., Pasquier, C., and Lopez-Perez, L. (2006a), “Co-expressed gene groups analysis (CGGA): An automatic tool for the interpretation of microarray experiments,” Journal of Integrative Bioinformatics, De Gruyter, 3, 1–12. https://doi.org/10.2390/biecoll-jib-2006-37.

Martinez, R., Pasquier, N., Pasquier, C., and Lopez-Perez, L. (2006b), “Interpreting microarray experiments via co-expressed gene groups analysis,” in 9th international conference of discovery science (icds’06), lecture notes in computer science, Barcelona: Springer Berlin Heidelberg, pp. 316–320. https://doi.org/10.1007/11893318_34.

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Claude Pasquier
Researcher in Computer Science / Computational Biology

Université côte d’Azur, CNRS, I3S Laboratory, Sophia Antipolis

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