sccomp
This is the released version of sccomp; for the devel version, see sccomp.
Differential Composition and Variability Analysis for Single-Cell Data
Bioconductor version: Release (3.23)
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("sccomp")):Stefano Mangiola, Alexandra J. Roth-Schulze, Marie Trussart, Enrique Zozaya-Valdés, Mengyao Ma, Zijie Gao, Alan F. Rubin, Terence P. Speed, Heejung Shim, Anthony T. Papenfuss. sccomp: Differential Composition and Variability Analysis for Single-Cell Data. doi:10.18129/B9.bioc.sccomp, R package version 2.4.0, https://bioconductor.org/packages/sccomp.
Generated from the package metadata; it may differ from the package's own citation.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
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 | ||
| LICENSE | Text |
Details
| biocViews | Bayesian, DifferentialExpression, FlowCytometry, Metagenomics, Regression, SingleCell, Software, Spatial |
| Version | 2.4.0 |
| In Bioconductor since | BioC 3.15 (R-4.2) (4.5 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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| Build Report | Build Report, r-universe |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | sccomp_2.4.0.tar.gz |
| Windows Binary (x86_64) | sccomp_2.4.0.zip |
| macOS Binary (big-sur-x86_64) | sccomp_2.4.0.tgz |
| macOS Binary (sonoma-arm64) | sccomp_2.4.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/sccomp |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/sccomp |
| Package Short Url | https://bioconductor.org/packages/sccomp/ |
| Package Downloads Report | Download Stats |