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Negative binomial model for scRNA-seq

Bioconductor version: Release (3.19)

A model designed for dimensionality reduction and batch effect removal for scRNA-seq data. It is designed to be massively parallelizable using shared objects that prevent memory duplication, and it can be used with different mini-batch approaches in order to reduce time consumption. It assumes a negative binomial distribution for the data with a dispersion parameter that can be both commonwise across gene both genewise.

Author: Federico Agostinis [aut, cre], Chiara Romualdi [aut], Gabriele Sales [aut], Davide Risso [aut]

Maintainer: Federico Agostinis <federico.agostinis at>

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biocViews BatchEffect, Coverage, GeneExpression, Regression, Sequencing, SingleCell, Software, Transcriptomics
Version 1.14.0
In Bioconductor since BioC 3.12 (R-4.0) (3.5 years)
License GPL-3
Depends R (>= 4.0), SummarizedExperiment
Imports methods, SingleCellExperiment, parallel, irlba, Matrix, DelayedArray, BiocSingular, SharedObject, stats
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Source Package NewWave_1.14.0.tar.gz
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