BinaryOutcome

A dataset containing phenotype data and high-dimensional mediators for binary outcome analysis.
The dataset was simulated using parameters generated from real data.

datasets

Allows to estimate and test high-dimensional mediation effects based on advanced mediator screening and penalized regression techniques. Methods used in the package refer to Zhang H, Zheng Y, Zhang Z, Gao T, Joyce B, Yoon G, Zhang W, Schwartz J, Just A, Colicino E, Vokonas P, Zhao L, Lv J, Baccarelli A, Hou L, Liu L. Estimating and Testing High-dimensional Mediation Effects in Epigenetic Studies. Bioinformatics. (2016) <doi:10.1093/bioinformatics/btw351>. PMID: 27357171.

Yinan Zheng

HIMA

High-Dimensional Mediation Analysis

Haixiang Zhang

Lifang Hou

Lei Liu

BinaryOutcome function

A list with the following components:<dl>
 <dt>PhenoData</dt>
<dd>A data frame containing:<dl>
 <dt>Treatment</dt>
<dd>treated (value = 1) or not treated (value = 0).</dd> <dt>Disease</dt>
<dd>binary outcome: diseased (value = 1) or healthy (value = 0).</dd> <dt>Sex</dt>
<dd>female (value = 1) or male (value = 0).</dd> <dt>Age</dt>
<dd>age of the participant.</dd> 
</dl></dd> <dt>Mediator</dt>
<dd>A matrix of high-dimensional mediators (rows: samples, columns: variables).</dd>
</dl>

Format

Binary Outcome Dataset for HIMA Demo — BinaryOutcome

A list with the following components:<dl>
 <dt>PhenoData</dt>
<dd>A data frame containing:<dl>
 <dt>Treatment</dt>
<dd>treated (value = 1) or not treated (value = 0).</dd>

 <dt>Disease</dt>
<dd>binary outcome: diseased (value = 1) or healthy (value = 0).</dd>

 <dt>Sex</dt>
<dd>female (value = 1) or male (value = 0).</dd>

 <dt>Age</dt>
<dd>age of the participant.</dd>

 
</dl></dd>

 <dt>Mediator</dt>
<dd>A matrix of high-dimensional mediators (rows: samples, columns: variables).</dd>


</dl>

BinaryOutcome: Binary Outcome Dataset for HIMA Demo

Description

Usage

Arguments

Format

Examples