_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-scmerge 1.26.0
Propagated dependencies: r-summarizedexperiment@1.40.0 r-singlecellexperiment@1.32.0 r-scran@1.38.0 r-scater@1.38.0 r-s4vectors@0.48.0 r-ruv@0.9.7.1 r-proxyc@0.5.2 r-m3drop@1.36.0 r-igraph@2.2.1 r-distr@2.9.7 r-delayedmatrixstats@1.32.0 r-delayedarray@0.36.0 r-cvtools@0.3.3 r-cluster@2.1.8.1 r-biocsingular@1.26.1 r-biocparallel@1.44.0 r-biocneighbors@2.4.0 r-batchelor@1.26.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/SydneyBioX/scMerge
Licenses: GPL 3
Synopsis: scMerge: Merging multiple batches of scRNA-seq data
Description:

Like all gene expression data, single-cell data suffers from batch effects and other unwanted variations that makes accurate biological interpretations difficult. The scMerge method leverages factor analysis, stably expressed genes (SEGs) and (pseudo-) replicates to remove unwanted variations and merge multiple single-cell data. This package contains all the necessary functions in the scMerge pipeline, including the identification of SEGs, replication-identification methods, and merging of single-cell data.

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