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multtest

Resampling-based multiple hypothesis testing

Bioconductor version: Release (3.17)

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.

Author: Katherine S. Pollard, Houston N. Gilbert, Yongchao Ge, Sandra Taylor, Sandrine Dudoit

Maintainer: Katherine S. Pollard <katherine.pollard at gladstone.ucsf.edu>

Citation (from within R, enter citation("multtest")):

Installation

To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("multtest")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

Reference Manual PDF

Details

biocViews DifferentialExpression, Microarray, MultipleComparison, Software
Version 2.56.0
In Bioconductor since BioC 1.6 (R-2.1) or earlier (> 18 years)
License LGPL
Depends R (>= 2.10), methods, BiocGenerics, Biobase
Imports survival, MASS, stats4
Linking To
Suggests snow
System Requirements
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Depends On Me aCGH, BicARE, iPAC, KCsmart, PREDA, rain, REDseq, siggenes, webbioc
Imports Me a4Base, ABarray, adSplit, ALDEx2, anota, anota2seq, ChIPpeakAnno, GUIDEseq, mAPKL, metabomxtr, microbiomeMarker, nethet, OCplus, phyloseq, RTopper, SingleCellSignalR, singleCellTK, synapter, webbioc, xcms
Suggests Me annaffy, ecolitk, factDesign, GOstats, GSEAlm, maigesPack, ropls, topGO
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package multtest_2.56.0.tar.gz
Windows Binary multtest_2.56.0.zip (64-bit only)
macOS Binary (x86_64) multtest_2.56.0.tgz
macOS Binary (arm64) multtest_2.56.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/multtest
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/multtest
Bioc Package Browser https://code.bioconductor.org/browse/multtest/
Package Short Url https://bioconductor.org/packages/multtest/
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