tradeSeq
This package is for version 3.14 of Bioconductor; for the stable, up-to-date release version, see tradeSeq.
trajectory-based differential expression analysis for sequencing data
Bioconductor version: 3.14
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 berkeley.edu>
citation("tradeSeq")
):
Installation
To install this package, start R (version "4.1") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
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")
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 | ||
NEWS | Text | |
LICENSE | Text |
Details
biocViews | Clustering, DifferentialExpression, GeneExpression, MultipleComparison, RNASeq, Regression, Sequencing, SingleCell, Software, TimeCourse, Transcriptomics, Visualization |
Version | 1.8.0 |
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 |
System Requirements | |
URL | https://statomics.github.io/tradeSeq/index.html |
Bug Reports | https://github.com/statOmics/tradeSeq/issues |
See More
Suggests | knitr, rmarkdown, testthat, covr, clusterExperiment |
Linking To | |
Enhances | |
Depends On Me | OSCA.advanced |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | tradeSeq_1.8.0.tar.gz |
Windows Binary | tradeSeq_1.8.0.zip |
macOS 10.13 (High Sierra) | tradeSeq_1.8.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/tradeSeq |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/tradeSeq |
Bioc Package Browser | https://code.bioconductor.org/browse/tradeSeq/ |
Package Short Url | https://bioconductor.org/packages/tradeSeq/ |
Package Downloads Report | Download Stats |
Old Source Packages for BioC 3.14 | Source Archive |