recipe bioconductor-multtest

Resampling-based multiple hypothesis testing







biotools: multtest, doi: 10.1007/0-387-29362-0_15

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.

package bioconductor-multtest

(downloads) docker_bioconductor-multtest


2.44.0-0, 2.42.0-0, 2.40.0-1, 2.38.0-0, 2.36.0-0, 2.34.0-0, 2.32.0-0, 2.28.0-1, 2.28.0-0, 2.26.0-0

Required By


With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-multtest

and update with:

conda update bioconductor-multtest

or use the docker container:

docker pull<tag>

(see bioconductor-multtest/tags for valid values for <tag>)