Bioconductor version: Release (3.6)
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]
Maintainer: Davide Risso <risso.davide at gmail.com>
Citation (from within R,
enter citation("zinbwave")
):
To install this package, start R and enter:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("zinbwave")
HTML | R Script | zinbwave Vignette |
Reference Manual | ||
Text | NEWS |
biocViews | DimensionReduction, GeneExpression, RNASeq, Sequencing, SingleCell, Software, Transcriptomics |
Version | 1.0.0 |
License | Artistic-2.0 |
Depends | R (>= 3.4), methods, SummarizedExperiment, SingleCellExperiment |
Imports | copula, glmnet, BiocParallel, softImpute, stats, genefilter, edgeR |
LinkingTo | |
Suggests | knitr, rmarkdown, testthat, matrixStats, magrittr, scRNAseq, ggplot2, biomaRt, BiocStyle, Rtsne |
SystemRequirements | |
Enhances | |
URL | |
BugReports | https://github.com/drisso/zinbwave/issues |
Depends On Me | |
Imports Me | |
Suggests Me | splatter |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | zinbwave_1.0.0.tar.gz |
Windows Binary | zinbwave_1.0.0.zip |
Mac OS X 10.11 (El Capitan) | zinbwave_1.0.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/zinbwave |
Package Short Url | http://bioconductor.org/packages/zinbwave/ |
Package Downloads Report | Download Stats |
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