sccomp

This package is for version 3.21 of Bioconductor; for the stable, up-to-date release version, see sccomp.

Tests differences in cell-type proportion for single-cell data, robust to outliers

Bioconductor version: 3.21

A robust and outlier-aware method for testing differences in cell-type proportion in single-cell data. This model can infer changes in tissue composition and heterogeneity, and can produce realistic data simulations based on any existing dataset. This model can also transfer knowledge from a large set of integrated datasets to increase accuracy further.

Author: Stefano Mangiola [aut, cre]

Maintainer: Stefano Mangiola <mangiolastefano at gmail.com>

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")
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 HTML R Script

Reference Manual PDF

LICENSE Text

Need some help? Ask on the Bioconductor Support site!

Details

biocViews Bayesian, DifferentialExpression, FlowCytometry, Metagenomics, Regression, SingleCell, Software, Spatial

Version 2.0.0

In Bioconductor since BioC 3.15 (R-4.2) (3.5 years)

License GPL-3

Depends R (>= 4.3.0)

Imports instantiate (>= 0.2.3), stats, SingleCellExperiment, parallel, dplyr, tidyr, purrr, magrittr, rlang, tibble, boot, lifecycle, tidyselect, utils, ggplot2, ggrepel, patchwork, forcats, readr, scales, stringr, glue, crayon

System Requirements CmdStan (https://mc-stan.org/users/interfaces/cmdstan)

URL https://github.com/MangiolaLaboratory/sccomp

Bug Reports https://github.com/MangiolaLaboratory/sccomp/issues

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

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Package Archives

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

Source Package sccomp_2.0.0.tar.gz

Windows Binary (x86_64) sccomp_2.0.0.zip

macOS Binary (x86_64) sccomp_2.0.0.tgz

macOS Binary (arm64) sccomp_2.0.0.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/

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