doi:10.1038/s43587-023-00514-x> for a full description of the methodology.">

scDiffCom: Differential Analysis of Intercellular Communication from scRNA-Seq Data (original) (raw)

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 human, mouse and rat) 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. (2023) <doi:10.1038/s43587-023-00514-x> for a full description of the methodology.

Version: 1.0.0
Depends: R (≥ 4.0.0)
Imports: data.table, DelayedArray, future, future.apply, magrittr, methods, Seurat (≥ 4.0.0), stats, utils
Suggests: biomaRt, covr, DT, ggplot2, GOSemSim, igraph, kableExtra, KEGGREST, knitr, ontologyIndex, ontoProc, pkgdown, plotly, RColorBrewer, rmarkdown, rrvgo, spelling, shiny, shinythemes, shinyWidgets, SingleCellSignalR, testthat (≥ 3.0.0), visNetwork
Published: 2023-11-03
DOI: 10.32614/CRAN.package.scDiffCom
Author: Cyril Lagger ORCID iD [aut, cre], Eugen Ursu [aut], Anais Equey [ctb]
Maintainer: Cyril Lagger <lagger.cyril at gmail.com>
License: MIT + file
URL: https://cyrillagger.github.io/scDiffCom/
NeedsCompilation: no
Language: en-US
Materials: README NEWS
CRAN checks: scDiffCom results

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