summary_lucid: Summarize results for integrative clustering

Description Usage Arguments Value Author(s) References Examples

View source: R/summary_lucid.R

Description

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

Usage

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Arguments

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

Value

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

Author(s)

Cheng Peng, Zhao Yang, David V. Conti

References

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.

Examples

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# 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)

USCbiostats/LUCid documentation built on Feb. 22, 2020, 8:57 p.m.