Current projects

Methodology

  • Association analysis of high dimensional covariate data with one or multiple correlated outcomes
  • Extensions of O2PLS and Probabilistic O2PLS
  • An asymptotic inference framework for Probabilistic O2PLS

Applications

  • Integrating multiple omics data to model and predict MSA
  • Integrating RNA-seq and ChIP-seq data in a case-control study
  • Associating multiple atherosclerosis markers with genetic SNPs

Software

  • OmicsPLS R package
  • PO2PLS R package

Old projects

Methodology

  • The Probabilistic O2PLS framework for diverse omics datasets
  • Probabilistic PLS as probabilistic alternative for Partial Least Squares, including asymptotic standard errors
  • O2PLS as data integration method in large population studies

Applications

  • Integration of longitudinal family data on Genetics, Methylation and triglyceride levels
  • Statistical integration of Genetic-glycan and Transcriptomic-metabolomic data with Probabilistic O2PLS
  • Modeling joint relationships between IgG1 and IgG2 glycomics data with Probabilistic PLS
  • Integrating Genetic and Glycomics data with O2PLS
  • Integrating Transcriptomics and Metabolomics data with O2PLS