tradeSeq

DOI: 10.18129/B9.bioc.tradeSeq    

This is the development version of tradeSeq; for the stable release version, see tradeSeq.

trajectory-based differential expression analysis for sequencing data

Bioconductor version: Development (3.12)

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 [ctb], Lieven Clement [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 "4.0") and enter:

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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

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")

 

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
Text   LICENSE

Details

biocViews Clustering, DifferentialExpression, GeneExpression, MultipleComparison, RNASeq, Regression, Sequencing, SingleCell, Software, TimeCourse, Transcriptomics, Visualization
Version 1.3.13
In Bioconductor since BioC 3.10 (R-3.6) (0.5 years)
License MIT + file LICENSE
Depends R (>= 3.6)
Imports mgcv, edgeR, SingleCellExperiment, SummarizedExperiment, slingshot, magrittr, RColorBrewer, BiocParallel, Biobase, pbapply, ggplot2, princurve, methods, monocle, igraph, S4Vectors, tibble, Matrix, matrixStats
LinkingTo
Suggests knitr, rmarkdown, testthat, covr, clusterExperiment, viridis
SystemRequirements
Enhances
URL https://statomics.github.io/tradeSeq/index.html
BugReports https://github.com/statOmics/tradeSeq/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

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

Source Package tradeSeq_1.3.13.tar.gz
Windows Binary tradeSeq_1.3.13.zip
macOS 10.13 (High Sierra) tradeSeq_1.3.13.tgz
Source Repository git clone https://git.bioconductor.org/packages/tradeSeq
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/tradeSeq
Package Short Url https://bioconductor.org/packages/tradeSeq/
Package Downloads Report Download Stats

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