_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-monocle3 1.3.7-1.98402ed
Propagated dependencies: r-assertthat@0.2.1 r-batchelor@1.26.0 r-biobase@2.70.0 r-biocgenerics@0.56.0 r-biocparallel@1.44.0 r-delayedarray@0.36.0 r-delayedmatrixstats@1.32.0 r-digest@0.6.39 r-dplyr@1.2.0 r-future@1.69.0 r-ggplot2@4.0.2 r-ggrastr@1.0.2 r-ggrepel@0.9.7 r-grr@0.9.5 r-hdf5array@1.38.0 r-igraph@2.2.2 r-irlba@2.3.7 r-leidenbase@0.1.36 r-limma@3.66.0 r-lme4@1.1-38 r-lmtest@0.9-40 r-mass@7.3-65 r-matrix@1.7-4 r-openssl@2.3.5 r-pbapply@1.7-4 r-pbmcapply@1.5.1 r-pheatmap@1.0.13 r-plotly@4.12.0 r-plyr@1.8.9 r-proxy@0.4-29 r-pscl@1.5.9 r-purrr@1.2.1 r-rann@2.6.2 r-rcolorbrewer@1.1-3 r-rcpp@1.1.1 r-rcppannoy@0.0.23 r-rcpphnsw@0.6.0 r-reshape2@1.4.5 r-rhpcblasctl@0.23-42 r-rsample@1.3.2 r-rtsne@0.17 r-s4vectors@0.48.0 r-sf@1.1-0 r-shiny@1.11.1 r-singlecellexperiment@1.32.0 r-slam@0.1-55 r-spdep@1.4-2 r-speedglm@0.3-5 r-stringr@1.6.0 r-summarizedexperiment@1.40.0 r-tibble@3.3.1 r-tidyr@1.3.2 r-uwot@0.2.4 r-viridis@0.6.5
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://github.com/cole-trapnell-lab/monocle3
Licenses: Expat
Build system: r
Synopsis: Analysis toolkit for single-cell RNA-Seq data
Description:

Monocle 3 performs clustering, differential expression and trajectory analysis for single-cell expression experiments. It orders individual cells according to progress through a biological process, without knowing ahead of time which genes define progress through that process. Monocle 3 also performs differential expression analysis, clustering, visualization, and other useful tasks on single-cell expression data. It is designed to work with RNA-Seq data, but could be used with other types as well.

Total packages: 1