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tradeSeq

trajectory-based differential expression analysis for sequencing data

Bioconductor version: 3.23 · Package version: 1.26.0

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.

Installation

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

BiocManager::install("tradeSeq")

Details

MaintainerHector Roux de Bezieux <hector.rouxdebezieux@berkeley.edu>
AuthorKoen Van den Berge [aut], Hector Roux de Bezieux [aut, cre] (ORCID: <https://orcid.org/0000-0002-1489-8339>), Kelly Street [aut, ctb], Lieven Clement [aut, ctb], Sandrine Dudoit [ctb]
LicenseMIT + file LICENSE
URLhttps://statomics.github.io/tradeSeq/index.html
Bug Reportshttps://github.com/statOmics/tradeSeq/issues
Downloads rank1508
Source branchRELEASE_3_23
biocViewsClustering, DifferentialExpression, GeneExpression, MultipleComparison, RNASeq, Regression, Sequencing, SingleCell, Software, TimeCourse, Transcriptomics, Visualization

Documentation

Download

Dependencies

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, DelayedMatrixStats

Reverse dependencies

Suggests Me (1): blase