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tradeSeq

trajectory-based differential expression analysis for sequencing data


Bioconductor version: Release (3.18)

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 [aut, ctb], Lieven Clement [aut, ctb], Sandrine Dudoit [ctb]

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

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

Installation

To install this package, start R (version "4.3") and enter:


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

Details

biocViews Clustering, DifferentialExpression, GeneExpression, MultipleComparison, RNASeq, Regression, Sequencing, SingleCell, Software, TimeCourse, Transcriptomics, Visualization
Version 1.16.0
In Bioconductor since BioC 3.10 (R-3.6) (4.5 years)
License MIT + file LICENSE
Depends R (>= 3.6)
Imports mgcv, edgeR, SingleCellExperiment, SummarizedExperiment, slingshot, magrittr, RColorBrewer, BiocParallel, Biobase, pbapply, igraph, ggplot2, princurve, methods, S4Vectors, tibble, Matrix, TrajectoryUtils, viridis, matrixStats, MASS
System Requirements
URL https://statomics.github.io/tradeSeq/index.html
Bug Reports https://github.com/statOmics/tradeSeq/issues
See More
Suggests knitr, rmarkdown, testthat, covr, clusterExperiment, DelayedMatrixStats
Linking To
Enhances
Depends On Me OSCA.advanced
Imports Me
Suggests Me
Links To Me
Build Report Build Report

Package Archives

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

Source Package tradeSeq_1.16.0.tar.gz
Windows Binary tradeSeq_1.16.0.zip
macOS Binary (x86_64) tradeSeq_1.16.0.tgz
macOS Binary (arm64) tradeSeq_1.16.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/tradeSeq
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/tradeSeq
Bioc Package Browser https://code.bioconductor.org/browse/tradeSeq/
Package Short Url https://bioconductor.org/packages/tradeSeq/
Package Downloads Report Download Stats