_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-coseq 1.34.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-scales@1.4.0 r-s4vectors@0.48.0 r-rmixmod@2.1.10 r-mvtnorm@1.3-3 r-htsfilter@1.50.0 r-htscluster@2.0.11 r-ggplot2@4.0.1 r-edger@4.8.0 r-e1071@1.7-16 r-deseq2@1.50.2 r-corrplot@0.95 r-compositions@2.0-9 r-capushe@1.1.3 r-biocparallel@1.44.0
Channel: guix-bioc
Location: guix-bioc/packages/c.scm (guix-bioc packages c)
Home page: https://bioconductor.org/packages/coseq
Licenses: GPL 3
Synopsis: Co-Expression Analysis of Sequencing Data
Description:

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.

Total results: 1