DOI: 10.18129/B9.bioc.tradeSeq    

This package is for version 3.10 of Bioconductor; for the stable, up-to-date release version, see tradeSeq.

trajectory-based differential expression analysis for sequencing data

Bioconductor version: 3.10

tradeSeq provides a flexible method for finding genes that are differentially expressed along one or multiple trajectories, using a variety of tests suited to answer questions of interest, e.g. the discovery of genes that whose expression is associated with pseudotime, or who are differentially expressed (in a specific region) along the trajectory. It fits a 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 [ctb], Sandrine Dudoit [ctb]

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

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


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biocViews Clustering, DifferentialExpression, GeneExpression, MultipleComparison, RNASeq, Regression, Sequencing, SingleCell, Software, TimeCourse, Transcriptomics, Visualization
Version 1.0.1
In Bioconductor since BioC 3.10 (R-3.6) (< 6 months)
License MIT + file LICENSE
Depends R (>= 3.6)
Imports mgcv, edgeR, SingleCellExperiment, SummarizedExperiment, slingshot, magrittr, RColorBrewer, clusterExperiment, BiocParallel, pbapply, ggplot2, princurve, methods, S4Vectors
Suggests knitr, rmarkdown, cowplot, dplyr, tidyr, testthat
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