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r-bioc-multtest package

r-bioc-multtest 2.56.0-1 source package in Ubuntu

Changelog

r-bioc-multtest (2.56.0-1) unstable; urgency=medium

  * New upstream version
  * Standards-Version: 4.6.2 (routine-update)
  * Reduce piuparts noise in transitions (routine-update)
  * Add debian/tests/autopkgtest-pkg-r.conf

 -- Andreas Tille <email address hidden>  Thu, 20 Jul 2023 22:59:50 +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
Mantic release universe misc

Downloads

File Size SHA-256 Checksum
r-bioc-multtest_2.56.0-1.dsc 2.1 KiB aedefc2aea3c87045651878edf9076df2e33dbd2ef9a5bf3773d5d2899c9275f
r-bioc-multtest_2.56.0.orig.tar.gz 1.2 MiB bf6a2f9c3666c7585e34305da503280ed3d2ab650165f8db17155c3f2fa286a5
r-bioc-multtest_2.56.0-1.debian.tar.xz 3.4 KiB 574f641f6eb5fed8e7d11b5d966aaab6f5756774f5024b5bc03df8ff8a535c77

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