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sccomp

This is the development version of sccomp; for the stable release version, see sccomp.

Differential Composition and Variability Analysis for Single-Cell Data


Bioconductor version: Development (3.22)

Comprehensive R package for differential composition and variability analysis in single-cell RNA sequencing, CyTOF, and microbiome data. Provides robust Bayesian modeling with outlier detection, random effects, and advanced statistical methods for cell type proportion analysis. Features include probabilistic outlier identification, mixed-effect modeling, differential variability testing, and comprehensive visualization tools. Perfect for cancer research, immunology, developmental biology, and single-cell genomics applications.

Author: Stefano Mangiola [aut, cre], Alexandra J. Roth-Schulze [aut], Marie Trussart [aut], Enrique Zozaya-Valdés [aut], Mengyao Ma [aut], Zijie Gao [aut], Alan F. Rubin [aut], Terence P. Speed [aut], Heejung Shim [aut], Anthony T. Papenfuss [aut]

Maintainer: Stefano Mangiola <stefano.mangiola at unimelb.edu.au>

Citation (from within R, enter citation("sccomp")):

Installation

To install this package, start R (version "4.5") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("sccomp")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("sccomp")
sccomp: Differential Composition and Variability Analysis for Single-Cell Data HTML R Script
Reference Manual PDF
LICENSE Text

Details

biocViews Bayesian, DifferentialExpression, FlowCytometry, Metagenomics, Regression, SingleCell, Software, Spatial
Version 2.1.16
In Bioconductor since BioC 3.15 (R-4.2) (3 years)
License GPL-3
Depends R (>= 4.3.0), instantiate (>= 0.2.3)
Imports stats, boot, utils, scales, lifecycle, rlang, tidyselect, magrittr, crayon, cli, fansi, dplyr, tidyr, purrr, tibble, ggplot2, ggrepel, patchwork, forcats, readr, stringr, glue, SingleCellExperiment
System Requirements CmdStan (https://mc-stan.org/users/interfaces/cmdstan), C++14
URL https://github.com/MangiolaLaboratory/sccomp
Bug Reports https://github.com/MangiolaLaboratory/sccomp/issues
See More
Suggests knitr, rmarkdown, BiocStyle, testthat (>= 3.0.0), markdown, loo, prettydoc, SeuratObject, tidyseurat, tidySingleCellExperiment, bayesplot, posterior
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package sccomp_2.1.16.tar.gz
Windows Binary (x86_64) sccomp_2.1.16.zip
macOS Binary (x86_64) sccomp_2.1.16.tgz
macOS Binary (arm64) sccomp_2.1.16.tgz
Source Repository git clone https://git.bioconductor.org/packages/sccomp
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/sccomp
Bioc Package Browser https://code.bioconductor.org/browse/sccomp/
Package Short Url https://bioconductor.org/packages/sccomp/
Package Downloads Report Download Stats