This is the released version of zinbwave; for the devel version, see zinbwave.
Zero-Inflated Negative Binomial Model for RNA-Seq DataBioconductor version: Release (3.21)
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 (from within R, entercitation("zinbwave")
): Installation
To install this package, start R (version "4.5") 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.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("zinbwave")
Details biocViews DimensionReduction, GeneExpression, ImmunoOncology, RNASeq, Sequencing, SingleCell, Software, Transcriptomics Version 1.30.0 In Bioconductor since BioC 3.6 (R-3.4) (7.5 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 benchdamic, 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.
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