Bioconductor/R package zinbwave: Zero-Inflated Negative Binomial Model for RNA-Seq Data. 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.
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References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Jia, Chen: Kinetic foundation of the zero-inflated negative binomial model for single-cell RNA sequencing data (2020)
- Dudoit, Sandrine; Gilbert, Houston N.; van der Laan, Mark J.: Resampling-based empirical Bayes multiple testing procedures for controlling generalized tail probability and expected value error rates: focus on the false discovery rate and simulation study (2008)