1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
|
Source: r-bioc-multtest
Standards-Version: 4.7.3
Maintainer: Debian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
Uploaders:
Andreas Tille <tille@debian.org>,
Section: gnu-r
Testsuite: autopkgtest-pkg-r
Build-Depends:
debhelper-compat (= 13),
dh-r,
r-base-dev,
r-bioc-biocgenerics,
r-bioc-biobase,
r-cran-survival,
r-cran-mass,
architecture-is-64-bit,
architecture-is-little-endian,
Vcs-Browser: https://salsa.debian.org/r-pkg-team/r-bioc-multtest
Vcs-Git: https://salsa.debian.org/r-pkg-team/r-bioc-multtest.git
Homepage: https://bioconductor.org/packages/multtest/
Rules-Requires-Root: no
Package: r-bioc-multtest
Architecture: any
Depends:
${R:Depends},
${shlibs:Depends},
${misc:Depends},
Recommends:
${R:Recommends},
Suggests:
${R:Suggests},
Description: Bioconductor resampling-based multiple hypothesis testing
Non-parametric bootstrap and permutation resampling-based multiple
testing procedures (including empirical Bayes methods) for controlling
the family-wise error rate (FWER), generalized family-wise error rate
(gFWER), tail probability of the proportion of false positives (TPPFP),
and false discovery rate (FDR). Several choices of bootstrap-based null
distribution are implemented (centered, centered and scaled,
quantile-transformed). Single-step and step-wise methods are available.
Tests based on a variety of t- and F-statistics (including t-statistics
based on regression parameters from linear and survival models as well
as those based on correlation parameters) are included. When probing
hypotheses with t-statistics, users may also select a potentially faster
null distribution which is multivariate normal with mean zero and
variance covariance matrix derived from the vector influence function.
Results are reported in terms of adjusted p-values, confidence regions
and test statistic cutoffs. The procedures are directly applicable to
identifying differentially expressed genes in DNA microarray
experiments.
|
