scDiffCom: Differential Analysis of Intercellular Communication from scRNA-Seq Data

Analysis tools to investigate changes in intercellular communication from scRNA-seq data. Using a Seurat object as input, the package infers which cell-cell interactions are present in the dataset and how these interactions change between two conditions of interest (e.g. young vs old). It relies on an internal database of ligand-receptor interactions (available for both human and mouse) that have been gathered from several published studies. Detection and differential analyses rely on permutation tests. The package also contains several tools to perform over-representation analysis and visualize the results. See Lagger, C. et al. (2021) <doi:10.1101/2021.08.13.456238> for a full description of the methodology.

Version: 0.1.0
Depends: R (≥ 4.0.0)
Imports: data.table, DelayedArray, future, future.apply, magrittr, methods, Seurat (≥ 4.0.0), stats, utils
Suggests: biomaRt, covr, ggplot2, igraph, kableExtra, KEGGREST, knitr, ontologyIndex, ontoProc, pkgdown, RColorBrewer, rmarkdown, spelling, SingleCellSignalR, testthat (≥ 3.0.0), visNetwork
Published: 2021-08-17
Author: Cyril Lagger ORCID iD [aut, cre], Eugen Ursu [aut], Anais Equey [ctb]
Maintainer: Cyril Lagger <lagger.cyril at gmail.com>
License: MIT + file LICENSE
URL: https://cyrillagger.github.io/scDiffCom/
NeedsCompilation: no
Language: en-US
Materials: README NEWS
CRAN checks: scDiffCom results

Downloads:

Reference manual: scDiffCom.pdf
Package source: scDiffCom_0.1.0.tar.gz
Windows binaries: r-devel: scDiffCom_0.1.0.zip, r-release: scDiffCom_0.1.0.zip, r-oldrel: not available
macOS binaries: r-release (arm64): scDiffCom_0.1.0.tgz, r-release (x86_64): scDiffCom_0.1.0.tgz, r-oldrel: scDiffCom_0.1.0.tgz

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