Age and sex simulated for 1000 subjects. Age was drawn from a gamma
distribution with mean 50 and variance 10. Sex was drawn from a Bernoulli
distribuiton with expectation 1/2.

datasets

Implementation of genetic association tests based on the rank based inverse normal transformation (INT). The primary contribution is an omnibus test, which synthesizes two complementary INT-based approaches. In simulations against phenotypes with skewed and heavy tailed residual distributions, the omnibus test provided valid inference in the absence of a genotypic effect, and provided power comparable to the more powerful of the component methods in the presence of a genotypic effect. Under these settings, standard linear regression often failed to control the type I error.

Zachary McCaw

RNOmni

Omnibus Test for Genetic Association Analysis using the Rank
Normal Transformation

X function

A numeric matrix with 1000 rows and 2 columns.<dl class="dl-horizontal">
 <dt>Age</dt><dd>Age.</dd>
 <dt>Sex</dt><dd>Sex.</dd>
</dl>

Format

Simulated Covariates — X

A numeric matrix with 1000 rows and 2 columns.<dl class='dl-horizontal'>
 <dt>Age</dt><dd>Age.</dd>
 <dt>Sex</dt><dd>Sex.</dd>
</dl>

X: Simulated Covariates

Description

Usage

Arguments

Format