LUCID with Multiple Omics Data

Implements Latent Unknown Clusters By Integrating Multi-omics Data (LUCID; Peng (2019) ) 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) .