sccomp
Robust Outlier-aware Estimation of Composition and Heterogeneity for Single-cell Data
Bioconductor version: Release (3.19)
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 | Clustering, GeneExpression, ImmunoOncology, Normalization, RNASeq, Sequencing, SingleCell, Software, Transcriptomics |
Version | 1.8.0 |
In Bioconductor since | BioC 3.15 (R-4.2) (2.5 years) |
License | GPL-3 |
Depends | R (>= 4.2.0) |
Imports | methods, Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1), rstantools (>= 2.1.1), rstan (>= 2.26.0), SeuratObject, SingleCellExperiment, parallel, dplyr, tidyr, purrr, magrittr, rlang, tibble, boot, lifecycle, stats, tidyselect, utils, ggplot2, ggrepel, patchwork, forcats, readr, scales, stringr, glue |
System Requirements | GNU make |
URL | https://github.com/stemangiola/sccomp |
Bug Reports | https://github.com/stemangiola/sccomp/issues |
See More
Suggests | BiocStyle, testthat (>= 3.0.0), markdown, knitr, loo, tidyseurat, tidySingleCellExperiment, prettydoc |
Linking To | BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), RcppParallel (>= 5.0.1), rstan (>= 2.26.0), StanHeaders (>= 2.26.0) |
Enhances | furrr, extraDistr |
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Imports Me | |
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Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | sccomp_1.8.0.tar.gz |
Windows Binary | sccomp_1.8.0.zip (64-bit only) |
macOS Binary (x86_64) | sccomp_1.8.0.tgz |
macOS Binary (arm64) | sccomp_1.8.0.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 |