Software

I provide either C or R code to facilitate implementation and/or reproducibility of (almost all!) the statistical methods developed in my publications alongside each here.

Many of the R packages and Shiny apps have been developed with Prof. Lorraine Brennan's Nutrition, Biomarkers and Health Research Group and are available at her group's software page.

The following are R packages and/or Shiny apps available for download from CRAN.

Majumdar K, Murphy T.B., Gormley I.C. (2022). betaclust: A Family of Beta Mixture Models for Clustering Beta-Valued DNA Methylation Data.
Finucane, K., Nyamundanda, G., Gormley, I.C., Fan, Y., Gallagher, W and Brennan, L. (2021) MetSizeR: an R package that provides a statistical tool for estimating sample sizes for metabolomic experiments. Shiny app available here.
D'Angelo, S., Brennan, L. and Gormley, I.C. (2020) multiMarker: Latent Variable Model to Infer Food Intake from Multiple Biomarkers. Associated Shiny app.
Murphy K., Murphy, T.B., Piccarreta, R, and Gormley, I.C. (2019) MEDseq: Mixtures of exponential-distance models with covariates.
D'Angelo, S., Gormley, I. C., McNulty, B. A., Nugent, A. P., Walton, J., Flynn, A., & Brennan, L. (2019). Combining biomarker and food intake data: calibration equations for citrus intake. The American journal of clinical nutrition. BioIntake Shiny app.
Murphy, K., Viroli, C. and Gormley, I.C. (2018). IMIFA: Infinite Mixtures of Infinite Factor Analysers and Related Models.
Gormley, I.C. and Murphy, T.B. (2016) MEclustnet: an R package to fit the mixture of experts latent position cluster model to network data.
McParland, D. and Gormley, I.C. (2015) clustMD: an R package for Model Based Clustering for Mixed Data.
Nyamundanda, G. and Brennan, L. and Gormley, I.C. (2010) MetabolAnalyze: an R package to fit probabilistic latent variable models for metabolomic data.