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This is the development version of zinbwave; for the stable release version, see zinbwave.

Zero-Inflated Negative Binomial Model for RNA-Seq Data

Bioconductor version: Development (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>

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


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biocViews DimensionReduction, GeneExpression, ImmunoOncology, RNASeq, Sequencing, SingleCell, Software, Transcriptomics
Version 1.27.0
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
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Suggests knitr, rmarkdown, testthat, matrixStats, magrittr, scRNAseq, ggplot2, biomaRt, BiocStyle, Rtsne, DESeq2, sparseMatrixStats
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Imports Me benchdamic, clusterExperiment, scBFA, singleCellTK, digitalDLSorteR, SpatialDDLS
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