sccomp
This is the released version of sccomp; for the devel version, see sccomp.
Robust Outlier-aware Estimation of Composition and Heterogeneity for Single-cell Data
Bioconductor version: Release (3.20)
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("sccomp")):
Installation
To install this package, start R (version "4.4") 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 |
Details
| biocViews | Bayesian, DifferentialExpression, Regression, SingleCell, Software |
| Version | 1.10.0 |
| 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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| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | sccomp_1.10.0.tar.gz |
| Windows Binary (x86_64) | sccomp_1.10.0.zip |
| macOS Binary (x86_64) | sccomp_1.10.0.tgz |
| macOS Binary (arm64) | sccomp_1.10.0.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/ |
| Package Downloads Report | Download Stats |