DOI: 10.18129/B9.bioc.coexnet    

This is the development version of coexnet; for the stable release version, see coexnet.

coexnet: An R package to build CO-EXpression NETworks from Microarray Data

Bioconductor version: Development (3.15)

Extracts the gene expression matrix from GEO DataSets (.CEL files) as a AffyBatch object. Additionally, can make the normalization process using two different methods (vsn and rma). The summarization (pass from multi-probe to one gene) uses two different criteria (Maximum value and Median of the samples expression data) and the process of gene differentially expressed analisys using two methods (sam and acde). The construction of the co-expression network can be conduced using two different methods, Pearson Correlation Coefficient (PCC) or Mutual Information (MI) and choosing a threshold value using a graph theory approach.

Author: Juan David Henao [aut,cre], Liliana Lopez-Kleine [aut], Andres Pinzon-Velasco [aut]

Maintainer: Juan David Henao <judhenaosa at>

Citation (from within R, enter citation("coexnet")):


To install this package, start R (version "4.2") and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


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biocViews DifferentialExpression, GeneExpression, GraphAndNetwork, Microarray, Network, NetworkInference, Normalization, Software, SystemsBiology
Version 1.17.0
In Bioconductor since BioC 3.6 (R-3.4) (4 years)
License LGPL
Depends R (>= 3.6)
Imports affy, siggenes, GEOquery, vsn, igraph, acde, Biobase, limma, graphics, stats, utils, STRINGdb, SummarizedExperiment, minet, rmarkdown
Suggests RUnit, BiocGenerics, knitr
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