Package: coexnet
Type: Package
Title: coexnet: An R package to build CO-EXpression NETworks from
        Microarray Data
Version: 1.12.0
Author: Juan David Henao [aut,cre], Liliana Lopez-Kleine [aut], Andres
        Pinzon-Velasco [aut]
Maintainer: Juan David Henao <judhenaosa@unal.edu.co>
Description: 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.
License: LGPL
LazyData: TRUE
Depends: R (>= 3.6)
Imports: affy, siggenes, GEOquery, vsn, igraph, acde, Biobase, limma,
        graphics, stats, utils, STRINGdb, SummarizedExperiment, minet,
        rmarkdown
Suggests: RUnit, BiocGenerics, knitr
VignetteBuilder: knitr
biocViews: GeneExpression, Microarray, DifferentialExpression,
        GraphAndNetwork, NetworkInference, SystemsBiology,
        Normalization, Network
RoxygenNote: 7.0.2
git_url: https://git.bioconductor.org/packages/coexnet
git_branch: RELEASE_3_12
git_last_commit: 10225db
git_last_commit_date: 2020-10-27
Date/Publication: 2020-10-27
NeedsCompilation: no
Packaged: 2020-10-27 23:20:29 UTC; biocbuild
Built: R 4.0.3; ; 2021-03-27 05:07:02 UTC; unix
