sim_data

This is an example dataset to illustrate LUCID model. It is simulated
by assuming there are 2 latent clusters in the data. We assume the exposures
are associated with latent cluster which ultimately affects the PFAS concentration
and liver injury in children. The latent clusters are also characterized by
differential levels of metabolites.

datasets

An implementation of estimating the Latent Unknown Clusters By Integrating Multi-omics Data (LUCID) model (Peng (2019) <doi:10.1093/bioinformatics/btz667>). LUCID conducts integrated clustering using exposures, omics information (and outcome information as an option). This package implements three different integration strategies for multi-omics data analysis within the LUCID framework: LUCID early integration (the original LUCID model), LUCID in parallel (intermediate integration), and LUCID in serial (late integration). Automated model selection for each LUCID model is available to obtain the optimal number of latent clusters, and an integrated imputation approach is implemented to handle sporadic and list-wise missingness in multi-omics data. Lasso-type regularity for exposure and omics features were added. S3 methods for summary and plotting functions were fixed. Fixed minor bugs.

Qiran Jia

LUCIDus

LUCID with Multiple Omics Data

Yinqi Zhao

David Conti

Jesse Goodrich

sim_data function

A list with 5 matrices corresponding to exposures (G), omics data (Z),
a continuous outcome, a binary outcome and 2 covariates (can be used either
as CoX or CoY). Each matrice contains 2000 observations.<dl>
<dt>G</dt>
<dd>10 exposures</dd><dt>Z</dt>
<dd>10 metabolites</dd><dt>Y_normal</dt>
<dd>Outcome, PFAS concentration in children</dd><dt>Y_bninary</dt>
<dd>Bianry outcome, liver injury status</dd><dt>Covariates</dt>
<dd>2 continous covariates, can be treated as either CoX or
CoY</dd><dt>X</dt>
<dd>Latent clusters</dd>
</dl>

Format

A simulated dataset for LUCID — sim_data

A list with 5 matrices corresponding to exposures (G), omics data (Z),
a continuous outcome, a binary outcome and 2 covariates (can be used either
as CoX or CoY). Each matrice contains 2000 observations.<dl>
<dt>G</dt>
<dd>10 exposures</dd>

<dt>Z</dt>
<dd>10 metabolites</dd>

<dt>Y_normal</dt>
<dd>Outcome, PFAS concentration in children</dd>

<dt>Y_bninary</dt>
<dd>Bianry outcome, liver injury status</dd>

<dt>Covariates</dt>
<dd>2 continous covariates, can be treated as either CoX or
CoY</dd>

<dt>X</dt>
<dd>Latent clusters</dd>


</dl>

sim_data: A simulated dataset for LUCID

Description

Usage

Arguments

Format