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zinbwave

Zero-Inflated Negative Binomial Model for RNA-Seq Data

Bioconductor version: 3.23 · Package version: 1.34.0

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.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("zinbwave")

Details

MaintainerDavide Risso <risso.davide@gmail.com>
AuthorDavide Risso [aut, cre, cph], Svetlana Gribkova [aut], Fanny Perraudeau [aut], Jean-Philippe Vert [aut], Clara Bagatin [aut]
LicenseArtistic-2.0
Bug Reportshttps://github.com/drisso/zinbwave/issues
Downloads rank1102
Source branchRELEASE_3_23
biocViewsDimensionReduction, GeneExpression, ImmunoOncology, RNASeq, Sequencing, SingleCell, Software, Transcriptomics

Documentation

Download

Dependencies

Depends: R (>= 3.4), methods, SummarizedExperiment, SingleCellExperiment

Imports: BiocParallel, softImpute, stats, genefilter, edgeR, Matrix

Suggests: knitr, rmarkdown, testthat, matrixStats, magrittr, scRNAseq, ggplot2, biomaRt, BiocStyle, Rtsne, DESeq2, sparseMatrixStats

Reverse dependencies

Imports Me (4): benchdamic, clusterExperiment, scBFA, singleCellTK

Suggests Me (2): MAST, splatter