DOI: 10.18129/B9.bioc.tradeSeq  

This package is for version 3.16 of Bioconductor; for the stable, up-to-date release version, see tradeSeq.

trajectory-based differential expression analysis for sequencing data

Bioconductor version: 3.16

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")):


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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


biocViews Clustering, DifferentialExpression, GeneExpression, MultipleComparison, RNASeq, Regression, Sequencing, SingleCell, Software, TimeCourse, Transcriptomics, Visualization
Version 1.12.0
In Bioconductor since BioC 3.10 (R-3.6) (3.5 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
Suggests knitr, rmarkdown, testthat, covr, clusterExperiment
Depends On Me OSCA.advanced
Imports Me
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