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Negative Binomial Additive Model for RNA-Seq Data

Bioconductor version: Release (3.19)

High-throughput sequencing experiments followed by differential expression analysis is a widely used approach to detect genomic biomarkers. A fundamental step in differential expression analysis is to model the association between gene counts and covariates of interest. NBAMSeq a flexible statistical model based on the generalized additive model and allows for information sharing across genes in variance estimation.

Author: Xu Ren [aut, cre], Pei Fen Kuan [aut]

Maintainer: Xu Ren <xuren2120 at>

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


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biocViews Coverage, DifferentialExpression, GeneExpression, RNASeq, Sequencing, Software
Version 1.20.0
In Bioconductor since BioC 3.9 (R-3.6) (5 years)
License GPL-2
Depends R (>= 3.6), SummarizedExperiment, S4Vectors
Imports DESeq2, mgcv (>= 1.8-24), BiocParallel, genefilter, methods, stats
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Source Package NBAMSeq_1.20.0.tar.gz
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