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
| Maintainer | Davide Risso <risso.davide@gmail.com> |
| Author | Davide Risso [aut, cre, cph], Svetlana Gribkova [aut], Fanny Perraudeau [aut], Jean-Philippe Vert [aut], Clara Bagatin [aut] |
| License | Artistic-2.0 |
| Bug Reports | https://github.com/drisso/zinbwave/issues |
| Downloads rank | 1102 |
| Source branch | RELEASE_3_23 |
| biocViews | DimensionReduction, GeneExpression, ImmunoOncology, RNASeq, Sequencing, SingleCell, Software, Transcriptomics |
Documentation
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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