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Co-Expression Analysis of Sequencing Data

Bioconductor version: Release (3.18)

Co-expression analysis for expression profiles arising from high-throughput sequencing data. Feature (e.g., gene) profiles are clustered using adapted transformations and mixture models or a K-means algorithm, and model selection criteria (to choose an appropriate number of clusters) are provided.

Author: Andrea Rau [cre, aut] , Cathy Maugis-Rabusseau [ctb], Antoine Godichon-Baggioni [ctb]

Maintainer: Andrea Rau <andrea.rau at inrae.fr>

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


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Reference Manual PDF


biocViews GeneExpression, ImmunoOncology, RNASeq, Sequencing, Software
Version 1.26.0
In Bioconductor since BioC 3.5 (R-3.4) (7 years)
License GPL-3
Depends R (>= 4.0.0), SummarizedExperiment, S4Vectors
Imports edgeR, DESeq2, capushe, Rmixmod, e1071, BiocParallel, ggplot2, scales, HTSFilter, corrplot, HTSCluster, grDevices, graphics, stats, methods, compositions, mvtnorm
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Suggests Biobase, knitr, rmarkdown, testthat, BiocStyle
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Source Package coseq_1.26.0.tar.gz
Windows Binary coseq_1.26.0.zip
macOS Binary (x86_64) coseq_1.26.0.tgz
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Bioc Package Browser https://code.bioconductor.org/browse/coseq/
Package Short Url https://bioconductor.org/packages/coseq/
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