sccomp

Differential Composition and Variability Analysis for Single-Cell Data

Bioconductor version: 3.23 · Package version: 2.4.0

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.

Installation

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

BiocManager::install("sccomp")

Details

Maintainer	Stefano Mangiola <stefano.mangiola@unimelb.edu.au>
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]
License	GPL-3
URL	https://github.com/MangiolaLaboratory/sccomp
Bug Reports	https://github.com/MangiolaLaboratory/sccomp/issues
System Requirements	CmdStan (https://mc-stan.org/users/interfaces/cmdstan), C++14
Downloads rank	343
Source branch	RELEASE_3_23
biocViews	Bayesian, DifferentialExpression, FlowCytometry, Metagenomics, Regression, SingleCell, Software, Spatial

Documentation

sccomp: Differential Composition and Variability Analysis for Single-Cell Data

Download

Source package

Dependencies

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

Suggests: knitr, rmarkdown, BiocStyle, testthat (>= 3.0.0), markdown, loo, prettydoc, SeuratObject, tidyseurat, tidySingleCellExperiment, bayesplot, posterior