Multivariate mixed model application to mass cytometry data (processed data)

This bachelor thesis demonstrates the results of mass cytometry data re-analysis using multivariate regression. I reanalyse a dataset by Palgen et al. (2019) using two models: a Poisson log-normal mixed model and a logistic linear mixed model from the R package ‘cytoeffect’ (Seiler et al., 2019). By exposing multivariate patterns and the associated uncertainty profiles in the data, the aim of this analysis is to replicate biological conclusions and uncover new biological findings.