Biomarker guided dietary intake 
Shiny app:
Bio-Intake (Biomarker guided dietary intake) allows users to upload mean daily self-reported citrus intake data (g/day) (estimated from food diaries) and computes calibrated intakes (g/day) based on a biomarker calibration equation. The biomarker based calibration equation was developed from urinary proline betaine and mean daily intake (estimated from a 4 day food diary) and is used to correct self-report estimates for measurement error.
Latent Variable Model to Infer Food Intake from Multiple Biomarkers
R package: 
A latent variable model based on factor analytic and mixture of experts models, designed to infer food intake from multiple biomarkers data. The model is framed within a Bayesian hierarchical framework, which provides flexibility to adapt to different biomarker distributions and facilitates prediction of the intake along with its associated uncertainty. Details are in D'Angelo, et al. (2020).
Probabilistic Latent Variable Models for Metabolomic Data
R package:
Fits probabilistic principal components analysis, probabilistic principal components and covariates analysis and mixtures of probabilistic principal components models to metabolomic spectral data.