 
  
 
   
   This package is for version 3.12 of Bioconductor; for the stable, up-to-date release version, see tradeSeq.
Bioconductor version: 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]
, 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")):
To install this package, start R (version "4.0") and enter:
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("tradeSeq")
    For older versions of R, please refer to the appropriate Bioconductor release.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("tradeSeq")
    
| 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 | 
| Reference Manual | ||
| Text | NEWS | |
| Text | LICENSE | 
| biocViews | Clustering, DifferentialExpression, GeneExpression, MultipleComparison, RNASeq, Regression, Sequencing, SingleCell, Software, TimeCourse, Transcriptomics, Visualization | 
| Version | 1.4.0 | 
| In Bioconductor since | BioC 3.10 (R-3.6) (1.5 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, viridis, matrixStats | 
| LinkingTo | |
| Suggests | knitr, rmarkdown, testthat, covr, clusterExperiment | 
| 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 | 
Follow Installation instructions to use this package in your R session.
| Source Package | tradeSeq_1.4.0.tar.gz | 
| Windows Binary | tradeSeq_1.3.13.zip | 
| macOS 10.13 (High Sierra) | tradeSeq_1.4.0.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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