summary_lucid: Summarize results for integrative clustering
In USCbiostats/LUCid: Latent Unknown Clustering with Integrated Data

Description Usage Arguments Value Author(s) References Examples

summary_lucid generates a summary for the results of integrative clustering based on an IntClust object.

1	summary_lucid(x, switch = FALSE, order = NULL)

`x`	An `IntClust` class object
`switch`	An indicator to do label switching or not, the default is FALSE
`order`	A customized order for label switching, a vector with a length of K; the default is NULL, which is a descending order in gamma

summary_lucid returns a list containing important outputs from an IntClust object.

`Beta`	Estimates of genetic effects, matrix
`Mu`	Estimates of cluster-specific biomarker means, matrix
`Gamma`	Estimates of cluster-specific disease risk, vector
`select_G`	A logical vector indicates non-zero genetic features
`select_Z`	A logical vector indicates non-zero bio-features
`No0G`	A total # of non-zero genetic features
`No0Z`	A total # of non-zero bio-features
`BIC`	Model BIC

Cheng Peng, Zhao Yang, David V. Conti

Cheng Peng, Jun Wang, Isaac Asante, Stan Louie, Ran Jin, Lida Chatzi, Graham Casey, Duncan C Thomas, David V Conti, A Latent Unknown Clustering Integrating Multi-Omics Data (LUCID) with Phenotypic Traits, Bioinformatics, , btz667, https://doi.org/10.1093/bioinformatics/btz667.

# For a testing dataset with 10 genetic features (5 causal) and 4 biomarkers (2 causal)

# Integrative clustering without feature selection
set.seed(10)
IntClusFit <- est_lucid(G=G1,Z=Z1,Y=Y1,K=2,family="binary",Pred=TRUE)

# Check important model outputs
summary_lucid(IntClusFit)