Package ‘ multtest ’
نویسندگان
چکیده
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 tand 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.
منابع مشابه
Bioconductor’s multtest package
1 Overview The multtest package contains a collection of functions for multiple hypothesis testing. These functions can be used to identify differentially expressed genes in microarray experiments, i.e., genes whose expression levels are associated with a response or covariate of interest. Introduction to multiple testing. This document provides a tutorial for using the multtest package. For a ...
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The Bioconductor R package multtest implements widely applicable resampling-based single-step and stepwise multiple testing procedures (MTP) for controlling a broad class of Type I error rates, in testing problems involving general data generating distributions (with arbitrary dependence structures among variables), null hypotheses, and test statistics [1, 2, 3, 4, 5]. The current version of mu...
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