Package: adaptest
Title: Data-Adaptive Statistics for High-Dimensional Multiple Testing
Version: 1.7.1
Authors@R: c(
    person("Weixin", "Cai", email = "wcai@berkeley.edu",
           role = c("aut", "cre", "cph"),
           comment = c(ORCID = "0000-0003-2680-3066")),
    person("Nima", "Hejazi", email = "nh@nimahejazi.org",
           role = "aut",
           comment = c(ORCID = "0000-0002-7127-2789")),
    person("Alan", "Hubbard", email = "hubbard@berkeley",
           role = c("ctb", "ths"),
           comment = c(ORCID = "0000-0002-3769-0127"))
    )
Description: Data-adaptive test statistics represent a general methodology for
    performing multiple hypothesis testing on effects sizes while maintaining
    honest statistical inference when operating in high-dimensional settings
    (<doi here>). The utilities provided here extend the use of this general
    methodology to many common data analytic challenges that arise in modern
    computational and genomic biology.
Depends: R (>= 3.6.0)
License: GPL-2
URL: https://github.com/wilsoncai1992/adaptest
BugReports: https://github.com/wilsoncai1992/adaptest/issues
Encoding: UTF-8
LazyData: true
Imports: methods, graphics, stats, utils, calibrate, origami (>=
        1.0.0), SummarizedExperiment, S4Vectors, tmle
Suggests: Matrix, testthat, rmarkdown, knitr, BiocStyle, SuperLearner,
        earth, gam, nnls, airway
VignetteBuilder: knitr
RoxygenNote: 6.1.1
biocViews: Genetics, GeneExpression, DifferentialExpression,
        Sequencing, Microarray, Regression, DimensionReduction,
        MultipleComparison
git_url: https://git.bioconductor.org/packages/adaptest
git_branch: master
git_last_commit: e11e11b
git_last_commit_date: 2019-12-30
Date/Publication: 2019-12-30
NeedsCompilation: no
Packaged: 2019-12-31 05:56:50 UTC; biocbuild
Author: Weixin Cai [aut, cre, cph] (<https://orcid.org/0000-0003-2680-3066>),
  Nima Hejazi [aut] (<https://orcid.org/0000-0002-7127-2789>),
  Alan Hubbard [ctb, ths] (<https://orcid.org/0000-0002-3769-0127>)
Maintainer: Weixin Cai <wcai@berkeley.edu>
Built: R 4.0.0; ; 2019-12-31 14:18:55 UTC; windows
