LUCID with Multiple Omics Data

Documentation for package ‘LUCIDus’ version 3.0.2

boot_lucid	Inference of LUCID model based on bootstrap resampling
check_na	Check missing patterns in one layer of omics data Z
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 based on LUCID model using new data of G,Z,(Y). If g_computation, predict cluster assignment, omics data, and outcome based on LUCID model using new data of G only This function can also be use to extract X assignment is using training data G,Z,Y as input.
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
simulated_HELIX_data	A simulated HELIX dataset for LUCID
sim_data	A simulated dataset for LUCID
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
tune_lucid	A wrapper function to perform model selection for LUCID