LUCIDus: Latent Unknown Clustering with Integrated Data

An implementation of LUCID model (Peng (2019) <doi:10.1093/bioinformatics/btz667>). LUCID conducts integrated clustering using exposures, omics data (and outcome of interest). An EM algorithm is implemented to estimate MLE of LUCID model. LUCID features integrated variable selection, incorporation of missing omics data, bootstrap inference and visualization via Sankey diagram.

Version: 2.1.5-1
Depends: R (≥ 3.6.0)
Imports: mclust, nnet, networkD3, boot, glasso, glmnet, jsonlite, progress
Suggests: knitr, testthat (≥ 3.0.0), rmarkdown
Published: 2022-04-06
Author: Yinqi Zhao, David V. Conti, Cheng Peng, Zhao Yang
Maintainer: Yinqi Zhao <yinqiz at>
License: GPL-3
NeedsCompilation: no
Citation: LUCIDus citation info
Materials: NEWS
CRAN checks: LUCIDus results


Reference manual: LUCIDus.pdf
Vignettes: LUCIDus: Latent Unknown Clustering with Integrated Data


Package source: LUCIDus_2.1.5-1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): LUCIDus_2.1.5-1.tgz, r-oldrel (arm64): LUCIDus_2.1.5-1.tgz, r-release (x86_64): LUCIDus_2.1.5-1.tgz, r-oldrel (x86_64): LUCIDus_2.1.5-1.tgz
Old sources: LUCIDus archive


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