tradeSeq
trajectory-based differential expression analysis for sequencing data
Bioconductor version: Release (3.19)
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 "4.4") 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 | 1.18.0 |
| In Bioconductor since | BioC 3.10 (R-3.6) (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, DelayedMatrixStats |
| 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_1.18.0.tar.gz |
| Windows Binary (x86_64) | tradeSeq_1.18.0.zip (64-bit only) |
| macOS Binary (x86_64) | tradeSeq_1.18.0.tgz |
| macOS Binary (arm64) | tradeSeq_1.18.0.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 3.19 | Source Archive |