Package: sccomp 2.4.0

Stefano Mangiola

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

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.

Authors: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]

sccomp_2.4.0.tar.gz
sccomp_2.4.0.zip(r-4.7)sccomp_2.4.0.zip(r-4.6)sccomp_2.4.0.zip(r-4.5)
sccomp_2.4.0.tgz(r-4.6-any)sccomp_2.4.0.tgz(r-4.5-any)
sccomp_2.4.0.tar.gz(r-4.7-any)sccomp_2.4.0.tar.gz(r-4.6-any)
sccomp_2.4.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
sccomp/json (API)

# Install 'sccomp' in R:
install.packages('sccomp', repos = c('https://bioc-release.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mangiolalaboratory/sccomp/issues

Datasets:

On BioConductor:sccomp-2.5.0(bioc 3.24)sccomp-2.4.0(bioc 3.23)

bayesianregressiondifferentialexpressionsinglecellmetagenomicsflowcytometryspatialbatch-correctioncompositioncytofdifferential-proportionmicrobiomemultilevelproportionsrandom-effectssingle-cellunwanted-variation

8.88 score 125 stars 169 scripts 460 downloads 16 exports 67 dependencies

Last updated from:e0b24e07d5 (on RELEASE_3_23). Checks:1 ERROR, 7 NOTE, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
bioc-checksERROR223
linux-devel-x86_64NOTE360
source / vignettesOK322
linux-release-x86_64NOTE358
macos-release-arm64NOTE320
macos-oldrel-arm64NOTE189
windows-develNOTE268
windows-releaseNOTE280
windows-oldrelNOTE289
wasm-releaseOK186

Exports:clear_stan_model_cacheplot_1D_intervalsplot_2D_intervalssccomp_boxplotsccomp_calculate_residualssccomp_estimatesccomp_predictsccomp_proportional_fold_changesccomp_remove_outlierssccomp_remove_unwanted_effectssccomp_remove_unwanted_variationsccomp_replicatesccomp_stan_models_cache_dirsccomp_testsccomp_themesimulate_data

Dependencies:abindBiobaseBiocGenericsbitbit64bootcallrclicliprcpp11crayonDelayedArraydplyrfansifarverforcatsfsgenericsGenomicRangesggplot2ggrepelgluegtablehmsinstantiateIRangesisobandlabelinglatticelifecyclemagrittrMatrixMatrixGenericsmatrixStatspatchworkpillarpkgconfigprettyunitsprocessxprogresspspurrrR6RColorBrewerRcppreadrrlangS4ArraysS4VectorsS7scalesSeqinfoSingleCellExperimentSparseArraystringistringrSummarizedExperimenttibbletidyrtidyselecttzdbutf8vctrsviridisLitevroomwithrXVector

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

Stefano Mangiola

Rendered fromintroduction.Rmdusingknitr::rmarkdownon May 30 2026.

Last update: 2025-07-18
Started: 2021-09-19