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LUCIDus (version 3.2.1)

LUCID with Multiple Omics Data

Description

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) . For the missing-data imputation mechanism, see Jia (2024) .

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Version

Install

install.packages('LUCIDus')

Monthly Downloads

365

Version

3.2.1

License

MIT + file LICENSE

Maintainer

Qiran Jia

Last Published

September 2nd, 2026

Functions in LUCIDus (3.2.1)

tune_lucid

Wrapper for LUCID Model and Penalty Tuning
summary.lucid_parallel

Summarize results of the parallel LUCID model
simulated_HELIX_data

A simulated HELIX dataset for LUCID
summary.lucid_serial

Summarize results of the serial LUCID model
summary_lucid

Summarize results of the early LUCID model
get_top_omics_features

Extract the top-N most important omics features from a fitted LUCID model
boot_lucid

Inference of LUCID model based on bootstrap resampling
get_cluster_assignment

Extract the hard cluster assignment from a fitted LUCID model
get_selected_G

Extract selected (retained) exposures from a fitted LUCID model
check_na

Classify each subject's omics missingness pattern
get_selected_Z

Extract selected (retained) omics features from a fitted LUCID model
analyze_missing_pattern

Describe the missing-data pattern of an omics matrix
check_imputation_quality

Check whether imputed values are distributionally plausible
lucid

Fit a lucid model for integrated analysis on exposure, outcome and multi-omics data, allowing for tuning
estimate_lucid

Fit LUCID models with one or multiple omics layers
print.sumlucid_parallel

Print the output of LUCID in a nicer table
plot_cluster_omic_profile

Plot per-cluster omics profiles
print.sumlucid_early

Print the output of LUCID in a nicer table
plot.lucid_parallel

Sankey diagram for a parallel-integration LUCID model (not yet implemented)
safe_impute

Single-value imputation that tolerates fully missing columns
plot.early_lucid

Visualize an early-integration LUCID model through a Sankey diagram
sim_data

A simulated dataset for LUCID
print.sumlucid_serial

Print the output of LUCID in a nicer table
predict_lucid

Predict Cluster Assignment and Outcome From a Fitted LUCID Model
plot.lucid_serial

Sankey diagram for a serial-integration LUCID model (not yet implemented)