sccomp

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

Robust Outlier-aware Estimation of Composition and Heterogeneity for Single-cell Data


Bioconductor version: Development (3.21)

A robust and outlier-aware method for testing differential tissue composition from 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")

# 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 HTML R Script
Reference Manual PDF

Details

biocViews Bayesian, DifferentialExpression, Regression, SingleCell, Software
Version 1.11.0
In Bioconductor since BioC 3.15 (R-4.2) (2.5 years)
License GPL-3
Depends R (>= 4.2.0)
Imports instantiate (>= 0.2.3), callr, fs, stats, SeuratObject, SingleCellExperiment, parallel, dplyr, tidyr, purrr, magrittr, rlang, tibble, boot, lifecycle, stats, tidyselect, utils, ggplot2, ggrepel, patchwork, forcats, readr, scales, stringr, glue, withr, digest
System Requirements CmdStan (https://mc-stan.org/users/interfaces/cmdstan)
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, knitr, 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_1.11.0.tar.gz
Windows Binary (x86_64)
macOS Binary (x86_64)
macOS Binary (arm64)
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