MultipleTesting

The MultipleTesting package offers common algorithms for p-value adjustment and combination as well as the estimation of the proportion π₀ of true null hypotheses.

Features

Adjustment of p-values

Bonferroni
Benjamini-Hochberg
Adaptive Benjamini-Hochberg with known π₀ or π₀ estimation method (see section below)
Benjamini-Yekutieli
Benjamini-Liu
Hochberg
Holm
Hommel
Sidak
Forward Stop
Barber-Candès

adjust(pvals, Bonferroni())
adjust(pvals, BenjaminiHochberg())
adjust(pvals, BenjaminiHochbergAdaptive(0.9))
adjust(pvals, BenjaminiHochbergAdaptive(Storey()))
adjust(pvals, BenjaminiYekutieli())
adjust(pvals, BenjaminiLiu())
adjust(pvals, Hochberg())
adjust(pvals, Holm())
adjust(pvals, Hommel())
adjust(pvals, Sidak())
adjust(pvals, ForwardStop())
adjust(pvals, BarberCandes())

The adjustment can also be performed on the k smallest out of n p-values:

adjust(pvals, n, PValueAdjustmentMethod)

Estimation of π₀

Storey
Storey's closed-form bootstrap
Least Slope
Two Step
RightBoundary (Storey's estimate with dynamically chosen λ)
Beta-Uniform Mixture (BUM)
Censored BUM
Flat Grenander
Oracle for known π₀

estimate_pi0(pvals, Storey())
estimate_pi0(pvals, StoreyBootstrap())
estimate_pi0(pvals, LeastSlope())
estimate_pi0(pvals, TwoStep())
estimate_pi0(pvals, TwoStep(0.05))
estimate_pi0(pvals, TwoStep(0.05, BenjaminiHochbergAdaptive(0.9))
estimate_pi0(pvals, RightBoundary())
estimate_pi0(pvals, CensoredBUM())
estimate_pi0(pvals, BUM())
estimate_pi0(pvals, FlatGrenander())
estimate_pi0(pvals, Oracle(0.9))

Combination of p-values

Fisher
Stouffer, optionally with weights
Logit
Tippett
Simes
Wilkinson
Minimum of adjusted p-values

combine(pvals, FisherCombination())
combine(pvals, StoufferCombination())
combine(pvals, weights, StoufferCombination())
combine(pvals, LogitCombination())
combine(pvals, TippettCombination())
combine(pvals, SimesCombination())
combine(pvals, WilkinsonCombination(rank))
combine(pvals, MinimumCombination(PValueAdjustment()))

Higher criticism

Higher criticism scores
Higher criticism threshold

estimate(pvals, HigherCriticismScores())
estimate(pvals, HigherCriticismThreshold())

Installation

The MultipleTesting package is part of the Julia ecosphere and the latest release version can be installed with

Pkg.add("MultipleTesting")

More details on packages and how to manage them can be found in the package section of the Julia documentation.

Feedback and Contributions

Contributions of any kind are very welcome. Please feel free to open pull requests or issues with your questions or ideas.

Package Status

The package uses semantic versioning.

juliadocsforks / multipletesting.jl Goto Github PK