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NBAMSeq

This is the development version of NBAMSeq; for the stable release version, see NBAMSeq.

Negative Binomial Additive Model for RNA-Seq Data


Bioconductor version: Development (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 gmail.com>

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

Installation

To install this package, start R (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("NBAMSeq")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

Reference Manual PDF

Details

biocViews Coverage, DifferentialExpression, GeneExpression, RNASeq, Sequencing, Software
Version 1.19.0
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
System Requirements
URL https://github.com/reese3928/NBAMSeq
Bug Reports https://github.com/reese3928/NBAMSeq/issues
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Suggests knitr, rmarkdown, testthat, ggplot2
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package
Windows Binary
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/NBAMSeq
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/NBAMSeq
Package Short Url https://bioconductor.org/packages/NBAMSeq/
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