Latent Unknown Clustering with Integrated Data (LUCID) is an integrative model to estimate latent unknown clusters using multi-view data (exposure, multiple types of omic data as well as outcome). It aims to both distinguish unique exposure effects and informative omic effects while jointly estimating subgroups of individuals relevant to the outcome of interest.

LUCIDus is an R package to implement the LUCID model. It features model estimation, model selection, model visualization, and inference based on bootstrap resampling. It also incorporates methods to deal with missingness in omics data.


  1. LUCIDus: website; code.
  2. LUCIDusM: an extension of LUCID incorporating multiple types of omic data in a parallel fashion. code


  1. LUCIDus: An R Package For Estimating Latent Unknown Clusters By Integrating Multi-omics Data (LUCID) With Phenotypic Traits. Under review for R Journal. Zhao, Y., Goodrich, J.A., Conti, D.V. Under review for R Journal. 2022.
  2. A latent unknown clustering integrating multi-omics data (LUCID) with phenotypic traits. Peng, C., Wang, J., Asante, I., Louie, S., Jin, R., Chatzi, L., Casey, G., Thomas, D.C. and Conti, D.V. Bioinformatics. February, 2020.


  1. LUCID, an integrative clustering model for multi omics data. Zhao, Y., Conti D.V. Platform presentation. International Genetic Epidemiology Society. October, 2022.
  2. Integrative clustering analysis for omics data with missingness and its application to prostate cancer. Zhao, Y., Darst, B., …, Conti, D.V., Haiman, C.A. Poster presentation. International Genetic Epidemiology Society. September, 2021.
  3. Latent Unknown Clustering With Integrated Omics Data (LUCID). Zhao, Y., Stratakis N., Conti D.V. Exposome Data Challenge. May, 2020.

Applied projects



Selected Publications

  1. Urinary metabolic biomarkers of diet quality in European children are associated with metabolic health. Stratakis, N,, Siskos, A.P., Papadopoulou, E., Nguyen, A.N., Zhao, Y., Margetaki, K., Lau, C.H., Coen, M., Maitre, L., Fernández-Barrés, S., Agier, L. Elife. January, 2022.
  2. In utero exposure to mercury is associated with increased susceptibility to liver injury and inflammation in childhood. Stratakis, N., Golden‐Mason, L., Margetaki, K., Zhao, Y., Valvi, D., Garcia, E., Maitre, L., Andrusaityte, S., Basagana, X., Borràs, E. and Bustamante, M. Hepatology. August, 2021.