sccomp

DOI: 10.18129/B9.bioc.sccomp    

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

Bioconductor version: Release (3.15)

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>

Installation

To install this package, start R (version "4.2") 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")

 

HTML	R Script	Overview of the sccomp package
PDF		Reference Manual

Details

biocViews	Clustering, GeneExpression, ImmunoOncology, Normalization, RNASeq, Sequencing, SingleCell, Software, Transcriptomics
Version	1.0.0
In Bioconductor since	BioC 3.15 (R-4.2) (0.5 years)
License	GPL-3
Depends	R (>= 4.1.0)
Imports	methods, Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1), rstantools (>= 2.1.1), rstan (>= 2.18.1), SeuratObject, SingleCellExperiment, parallel, dplyr, tidyr, purrr, magrittr, rlang, tibble, boot, lifecycle, stats, tidyselect, utils, ggplot2, ggrepel, patchwork, forcats, readr, scales, stringr
LinkingTo	BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), RcppParallel (>= 5.0.1), rstan (>= 2.18.1), StanHeaders (>= 2.18.0)
Suggests	BiocStyle, testthat (>= 3.0.0), markdown, ggplot2, knitr, tidyseurat, tidySingleCellExperiment
SystemRequirements	GNU make
Enhances	furrr, extraDistr
URL	https://github.com/stemangiola/sccomp
BugReports	https://github.com/stemangiola/sccomp/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	sccomp_1.0.0.tar.gz
Windows Binary	sccomp_1.0.0.zip
macOS Binary (x86_64)	sccomp_1.0.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/sccomp
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/sccomp
Package Short Url	https://bioconductor.org/packages/sccomp/
Package Downloads Report	Download Stats