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r-bioc-multtest package

r-bioc-multtest 2.52.0-1 source package in Ubuntu

Changelog

r-bioc-multtest (2.52.0-1) unstable; urgency=medium

  * New upstream version
  * Standards-Version: 4.6.1 (routine-update)
  * Reorder sequence of d/control fields by cme (routine-update)

 -- Andreas Tille <email address hidden>  Fri, 13 May 2022 13:43:19 +0200

Upload details

Uploaded by:
Debian R Packages Maintainers
Uploaded to:
Sid
Original maintainer:
Debian R Packages Maintainers
Architectures:
any
Section:
misc
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section

Downloads

File Size SHA-256 Checksum
r-bioc-multtest_2.52.0-1.dsc 2.1 KiB 3456831844551e31e5b81155d13b5c9ed56803be9266b6ae9fdc46397143724d
r-bioc-multtest_2.52.0.orig.tar.gz 1.2 MiB 02f5d868a59d849e7c9d528d7242843af2791312d36e5a5f9770f3307965fc0c
r-bioc-multtest_2.52.0-1.debian.tar.xz 3.3 KiB 93bbac1c2328b0871e532f413929ed37aea6ba333be17842ce9439f286d7323f

Available diffs

No changes file available.

Binary packages built by this source

r-bioc-multtest: 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.

r-bioc-multtest-dbgsym: debug symbols for r-bioc-multtest