zinbwave
Zero-Inflated Negative Binomial Model for RNA-Seq Data
Bioconductor version: Release (3.20)
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("zinbwave")
):
Installation
To install this package, start R (version "4.4") 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 | ||
NEWS | Text |
Details
biocViews | DimensionReduction, GeneExpression, ImmunoOncology, RNASeq, Sequencing, SingleCell, Software, Transcriptomics |
Version | 1.28.0 |
In Bioconductor since | BioC 3.6 (R-3.4) (7 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, sparseMatrixStats |
Linking To | |
Enhances | |
Depends On Me | |
Imports Me | clusterExperiment, scBFA, singleCellTK, SpatialDDLS |
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_1.28.0.tar.gz |
Windows Binary (x86_64) | zinbwave_1.28.0.zip |
macOS Binary (x86_64) | zinbwave_1.28.0.tgz |
macOS Binary (arm64) | zinbwave_1.27.0.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 |