Package: adaptest
Title: Data-Adaptive Statistics for High-Dimensional Multiple Testing
Version: 1.0.0
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"))
    )
Author: Weixin Cai [aut, cre, cph], Nima Hejazi [aut], Alan Hubbard [ctb, ths]
Maintainer: Weixin Cai <wcai@berkeley.edu>
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 (>= 3.5.0)
License: GPL-2
URL: https://github.com/wilsoncai1992/adaptest
BugReports: https://github.com/wilsoncai1992/adaptest/issues
Encoding: UTF-8
LazyData: true
Imports: origami (>= 1.0.0), tmle, calibrate, methods, graphics, stats,
        utils, SummarizedExperiment
Suggests: testthat, Matrix, SuperLearner, earth, gam, nnls, airway,
        rmarkdown, knitr, BiocStyle
VignetteBuilder: knitr
RoxygenNote: 6.0.1.9000
biocViews: Genetics, GeneExpression, DifferentialExpression,
        Sequencing, Microarray, Regression, DimensionReduction,
        MultipleComparison
NeedsCompilation: no
Packaged: 2018-05-01 04:33:04 UTC; biocbuild
Built: R 3.5.0; ; 2018-05-01 11:25:21 UTC; windows
