zinbwave

DOI: 10.18129/B9.bioc.zinbwave    

This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see zinbwave.

Zero-Inflated Negative Binomial Model for RNA-Seq Data

Bioconductor version: 3.15

Implements a general and flexible zero-inflated negative binomial model that can be used to provide a low-dimensional representations of single-cell RNA-seq data. The model accounts for zero inflation (dropouts), over-dispersion, and the count nature of the data. The model also accounts for the difference in library sizes and optionally for batch effects and/or other covariates, avoiding the need for pre-normalize the data.

Author: Davide Risso [aut, cre, cph], Svetlana Gribkova [aut], Fanny Perraudeau [aut], Jean-Philippe Vert [aut], Clara Bagatin [aut]

Maintainer: Davide Risso <risso.davide 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("zinbwave")

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("zinbwave")

 

HTML	R Script	zinbwave Vignette
PDF		Reference Manual
Text		NEWS

Details

biocViews	DimensionReduction, GeneExpression, ImmunoOncology, RNASeq, Sequencing, SingleCell, Software, Transcriptomics
Version	1.18.0
In Bioconductor since	BioC 3.6 (R-3.4) (5 years)
License	Artistic-2.0
Depends	R (>= 3.4), methods, SummarizedExperiment, SingleCellExperiment
Imports	BiocParallel, softImpute, stats, genefilter, edgeR, Matrix
LinkingTo
Suggests	knitr, rmarkdown, testthat, matrixStats, magrittr, scRNAseq, ggplot2, biomaRt, BiocStyle, Rtsne, DESeq2
SystemRequirements
Enhances
URL
BugReports	https://github.com/drisso/zinbwave/issues
Depends On Me
Imports Me	benchdamic, clusterExperiment, scBFA, singleCellTK
Suggests Me	MAST, splatter
Links To Me
Build Report

Package Archives

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

Source Package	zinbwave_1.18.0.tar.gz
Windows Binary	zinbwave_1.18.0.zip
macOS Binary (x86_64)	zinbwave_1.18.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/zinbwave
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/zinbwave
Package Short Url	https://bioconductor.org/packages/zinbwave/
Package Downloads Report	Download Stats