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zinbwave

Zero-Inflated Negative Binomial Model for RNA-Seq Data


Bioconductor version: Release (3.18)

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>

Citation (from within R, enter citation("zinbwave")):

Installation

To install this package, start R (version "4.3") 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")
zinbwave Vignette HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews DimensionReduction, GeneExpression, ImmunoOncology, RNASeq, Sequencing, SingleCell, Software, Transcriptomics
Version 1.24.0
In Bioconductor since BioC 3.6 (R-3.4) (6.5 years)
License Artistic-2.0
Depends R (>= 3.4), methods, SummarizedExperiment, SingleCellExperiment
Imports BiocParallel, softImpute, stats, genefilter, edgeR, Matrix
System Requirements
URL
Bug Reports https://github.com/drisso/zinbwave/issues
See More
Suggests knitr, rmarkdown, testthat, matrixStats, magrittr, scRNAseq, ggplot2, biomaRt, BiocStyle, Rtsne, DESeq2
Linking To
Enhances
Depends On Me
Imports Me benchdamic, clusterExperiment, scBFA, singleCellTK
Suggests Me MAST, splatter
Links To Me
Build Report Build Report

Package Archives

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

Source Package zinbwave_1.24.0.tar.gz
Windows Binary zinbwave_1.24.0.zip (64-bit only)
macOS Binary (x86_64) zinbwave_1.24.0.tgz
macOS Binary (arm64) zinbwave_1.24.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/zinbwave
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/zinbwave
Bioc Package Browser https://code.bioconductor.org/browse/zinbwave/
Package Short Url https://bioconductor.org/packages/zinbwave/
Package Downloads Report Download Stats