A simulated dataset containing one of the components to run lucid. The variables are as follows:

datasets

An implementation for the 'LUCID' model (Peng (2019) <doi:10.1093/bioinformatics/btz667>) to jointly estimate latent unknown clusters/subgroups with integrated data.
An EM algorithm is used to obtain the latent cluster assignment and model parameter estimates.
Feature selection is achieved by applying the L1 regularization method.

Yinqi Zhao

LUCIDus

Latent Unknown Clustering with Integrated Data

G1 function

A set with 3000 rows and 10 variables:<dl class="dl-horizontal">
 <dt>CG1 - CG5</dt><dd>Causal SNPs</dd>
 <dt>NG1 - NG5</dt><dd>Null SNPs</dd>
</dl>

Format

Genetic Features Set 1 — G1

A set with 3000 rows and 10 variables:<dl class='dl-horizontal'>
 <dt>CG1 - CG5</dt><dd>Causal SNPs</dd>
 <dt>NG1 - NG5</dt><dd>Null SNPs</dd>
</dl>

G1: Genetic Features Set 1

Description

Usage

Arguments

Format