summary.lucid_parallel

Summarize results of the parallel LUCID model

Implements Latent Unknown Clusters By Integrating Multi-omics Data
(LUCID; Peng (2019) <doi:10.1093/bioinformatics/btz667>) for integrative
clustering with exposures, multi-omics data, and health outcomes.
Supports three integration strategies: early, parallel, and serial.
Provides model fitting and tuning, lasso-type regularization for exposure
and omics feature selection, handling of missing data, including both
sporadic and complete-case patterns, prediction, and g-computation for
estimating causal effects of exposures, bootstrap inference for
uncertainty estimation, and S3 summary and plot methods. For the
multi-omics integration framework, see Jia (2024)
<https://journal.r-project.org/articles/RJ-2024-012/RJ-2024-012.pdf>.
For the missing-data imputation mechanism, see Jia (2024)
<doi:10.1093/bioadv/vbae123>.

Qiran Jia

LUCIDus

LUCID with Multiple Omics Data

Yinqi Zhao

David Conti

Jesse Goodrich

summary.lucid_parallel function

<dl><dt>object</dt>
<dd>A LUCID model fitted by <code>estimate_lucid</code></dd>
<dt>...</dt>
<dd>Additional argument <code>boot.se</code>, which can be an object
returned by <code>boot_lucid</code> to display bootstrap CIs in print output.</dd></dl>

Arguments

Summarize results of the parallel LUCID model — summary.lucid_parallel

<dl>

<dt>object</dt>
<dd>A LUCID model fitted by <code>estimate_lucid</code></dd>


<dt>...</dt>
<dd>Additional argument <code>boot.se</code>, which can be an object
returned by <code>boot_lucid</code> to display bootstrap CIs in print output.</dd>

</dl>

summary.lucid_parallel: Summarize results of the parallel LUCID model

Description

Usage

Value

Arguments