Package: tradeSeq
Type: Package
Title: trajectory-based differential expression analysis for sequencing
        data
Date: 2019-03-17
Version: 1.25.0
Authors@R: c(person("Koen", "Van den Berge", role = c("aut"),
                     email = "koen.vandenberge@ugent.be"),
              person("Hector", "Roux de Bezieux", role = c("aut", "cre"),
                     email = "hector.rouxdebezieux@berkeley.edu",
		     comment = c(ORCID = "0000-0002-1489-8339")),
		person("Kelly","Street", role = c("aut","ctb")),
		person("Lieven","Clement", role=c("aut","ctb")),
		person("Sandrine","Dudoit", role="ctb"))
Description: 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.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: false
URL: https://statomics.github.io/tradeSeq/index.html
Depends: R (>= 3.6)
Collate: 'AllGenerics.R' 'utils.R' 'associationTest.R'
        'clusterExpressionPatterns.R' 'conditionTest.R' 'data.R'
        'diffEndTest.R' 'earlyDETest.R' 'evaluateK.R' 'fitGAM.R'
        'getSmootherPvalues.R' 'getSmootherTestStats.R' 'nknots.R'
        'patternTest.R' 'plotGeneCount.R' 'plotSmoothers.R'
        'predictCells.R' 'predictSmooth.R' 'startVsEndTest.R'
RoxygenNote: 7.2.1
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
VignetteBuilder: knitr
biocViews: Clustering, Regression, TimeCourse, DifferentialExpression,
        GeneExpression, RNASeq, Sequencing, Software, SingleCell,
        Transcriptomics, MultipleComparison, Visualization
BugReports: https://github.com/statOmics/tradeSeq/issues
Config/pak/sysreqs: libglpk-dev libxml2-dev zlib1g-dev
Repository: https://bioc.r-universe.dev
Date/Publication: 2025-10-29 14:55:42 UTC
RemoteUrl: https://github.com/bioc/tradeSeq
RemoteRef: HEAD
RemoteSha: 4e786223c499f9a65c033f23acb6b771550586bc
NeedsCompilation: no
Packaged: 2025-11-23 13:51:37 UTC; root
Author: Koen 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]
Maintainer: Hector Roux de Bezieux <hector.rouxdebezieux@berkeley.edu>
Built: R 4.6.0; ; 2025-11-23 13:54:36 UTC; windows
