studies

datasets

Classical methods for combining summary data from genome-wide
association studies (GWAS) only use marginal genetic effects and power can
be compromised in the presence of heterogeneity. 'subgxe' is a R package
that implements p-value assisted subset testing for association (pASTA),
a method developed by Yu et al. (2019) <doi:10.1159/000496867>. pASTA
generalizes association analysis based on subsets by incorporating
gene-environment interactions into the testing procedure.

Alexander Rix

subgxe

Combine Multiple GWAS by Using Gene-Environment Interactions

Youfei Yu

studies function

A list of 5 <code>data.frames</code> with 12000 observations
(6000 cases, 6000 controls) on 4 variables:<dl class="dl-horizontal">
 <dt>D</dt><dd>Disease status. Numeric 0-1</dd>
 <dt>G</dt><dd>Genetic variant. Numeric 0-1</dd>
 <dt>E</dt><dd>Exposure. Numeric 0-1</dd>
 <dt>GbyE</dt><dd><code>G * E</code>. Either 1 or 0.</dd>
</dl>

Format

Synthetic data for subgxe — studies

A list of 5 <code>data.frames</code> with 12000 observations
(6000 cases, 6000 controls) on 4 variables:<dl class='dl-horizontal'>
 <dt>D</dt><dd>Disease status. Numeric 0-1</dd>
 <dt>G</dt><dd>Genetic variant. Numeric 0-1</dd>
 <dt>E</dt><dd>Exposure. Numeric 0-1</dd>
 <dt>GbyE</dt><dd><code>G * E</code>. Either 1 or 0.</dd>
</dl>

studies: Synthetic data for subgxe

Description

Usage

Arguments

Format