tradeSeq

DOI: 10.18129/B9.bioc.tradeSeq    

This package is for version 3.13 of Bioconductor; for the stable, up-to-date release version, see tradeSeq.

trajectory-based differential expression analysis for sequencing data

Bioconductor version: 3.13

tradeSeq provides a flexible method for fitting regression models that can be used to find genes that are differentially expressed along one or multiple lineages in a trajectory. Based on the fitted models, it uses a variety of tests suited to answer different questions of interest, e.g. the discovery of genes for which expression is associated with pseudotime, or which are differentially expressed (in a specific region) along the trajectory. It fits a negative binomial generalized additive model (GAM) for each gene, and performs inference on the parameters of the GAM.

Author: Koen Van den Berge [aut], Hector Roux de Bezieux [aut, cre] , Kelly Street [ctb], Lieven Clement [aut, ctb], Sandrine Dudoit [ctb]

Maintainer: Hector Roux de Bezieux <hector.rouxdebezieux at berkeley.edu>

Installation

To install this package, start R (version "4.1") and enter:

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

BiocManager::install("tradeSeq")

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

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("tradeSeq")

 

HTML		Differential expression across conditions
HTML	R Script	Monocle + tradeSeq
HTML	R Script	More details on working with fitGAM
HTML	R Script	The tradeSeq workflow
PDF		Reference Manual
Text		NEWS
Text		LICENSE

Details

biocViews	Clustering, DifferentialExpression, GeneExpression, MultipleComparison, RNASeq, Regression, Sequencing, SingleCell, Software, TimeCourse, Transcriptomics, Visualization
Version	1.6.0
In Bioconductor since	BioC 3.10 (R-3.6) (2 years)
License	MIT + file LICENSE
Depends	R (>= 3.6)
Imports	mgcv, edgeR, SingleCellExperiment, SummarizedExperiment, slingshot, magrittr, RColorBrewer, BiocParallel, Biobase, pbapply, ggplot2, princurve, methods, monocle, igraph, S4Vectors, tibble, Matrix, viridis, matrixStats
LinkingTo
Suggests	knitr, rmarkdown, testthat, covr, clusterExperiment
SystemRequirements
Enhances
URL	https://statomics.github.io/tradeSeq/index.html
BugReports	https://github.com/statOmics/tradeSeq/issues
Depends On Me	OSCA.advanced
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	tradeSeq_1.6.0.tar.gz
Windows Binary	tradeSeq_1.6.0.zip
macOS 10.13 (High Sierra)	tradeSeq_1.6.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/tradeSeq
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/tradeSeq
Package Short Url	https://bioconductor.org/packages/tradeSeq/
Package Downloads Report	Download Stats