R: LUCID with Multiple Omics Data

# LUCID with Multiple Omics Data

## Documentation for package ‘LUCIDus’ version 3.1.0

- DESCRIPTION file

## Help Pages

analyze_missing_pattern | Analyze missing data patterns in detail
boot_lucid | Inference of LUCID model based on bootstrap resampling
check_and_stabilize_sigma | Check matrix condition and stabilize if needed
check_convergence | Check convergence with both absolute and relative criteria
check_imputation_quality | Check quality of imputed data
check_na | Check missing patterns in omics data
estimate_lucid | Fit LUCID models with one or multiple omics layers
fill_data | Impute missing data by optimizing the likelihood function
gen_ci | generate bootstrp ci (normal, basic and percentile)
Istep_Z | I-step of LUCID
lucid | Fit a lucid model for integrated analysis on exposure, outcome and multi-omics data, allowing for tuning
plot | Visualize LUCID model through a Sankey diagram
predict_lucid | Predict Cluster Assignment and Outcome From a Fitted LUCID Model
print.sumlucid_early | Print the output of LUCID in a nicer table
print.sumlucid_parallel | Print the output of LUCID in a nicer table
print.sumlucid_serial | Print the output of LUCID in a nicer table
safe_impute | Safe imputation for edge cases
safe_log_sum_exp | Safe log-sum-exp computation
safe_normalize | Safe probability normalization
safe_solve | Safe matrix inversion with stability checks
simulated_HELIX_data | A simulated HELIX dataset for LUCID
sim_data | A simulated dataset for LUCID
summarize_missing_stats | Summarize missing-data patterns from check_na output
summary.early_lucid | Summarize results of the early LUCID model
summary.lucid_parallel | Summarize results of the parallel LUCID model
summary.lucid_serial | Summarize results of the serial LUCID model
summary_lucid | Summarize results of the early LUCID model
tune_lucid | Wrapper for LUCID Model and Penalty Tuning