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trajectory-based differential expression analysis for sequencing data

Bioconductor version: Release (3.19)

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>

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


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

if (!require("BiocManager", quietly = TRUE))


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


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

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


biocViews Clustering, DifferentialExpression, GeneExpression, MultipleComparison, RNASeq, Regression, Sequencing, SingleCell, Software, TimeCourse, Transcriptomics, Visualization
Version 1.18.0
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
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Follow Installation instructions to use this package in your R session.

Source Package tradeSeq_1.18.0.tar.gz
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macOS Binary (x86_64) tradeSeq_1.18.0.tgz
macOS Binary (arm64) tradeSeq_1.18.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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