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multtest (version 2.28.0)

Resampling-based multiple hypothesis testing

Description

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.

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Version

Monthly Downloads

236

Version

2.28.0

License

LGPL

Last Published

February 15th, 2017

Functions in multtest (2.28.0)

MTP-class

Class "MTP", classes and methods for multiple testing procedure output
MTP-methods

Methods for MTP and EBMTP objects in Package `multtest'
corr.null

Function to estimate a test statistics joint null distribution for t-statistics via the vector influence curve
boot.null

Non-parametric bootstrap resampling function in package `multtest'
ss.maxT

Procedures to perform multiple testing
MTP

A function to perform resampling-based multiple hypothesis testing
multtest-internal

Internal multtest functions and variables
meanX

Functions to create test statistic closures and apply them to data
wapply

Weighted version of the apply function
mt.maxT

Step-down maxT and minP multiple testing procedures
mt.plot

Plotting results from multiple testing procedures
mt.rawp2adjp

Adjusted p-values for simple multiple testing procedures
mt.reject

Identity and number of rejected hypotheses
EBMTP-class

Class "EBMTP", classes and methods for empirical Bayes multiple testing procedure output
fwer2gfwer

Function to compute augmentation MTP adjusted p-values
get.index

Function to compute indices for ordering hypotheses in Package 'multtest'
golub

Gene expression dataset from Golub et al. (1999)