For an in-depth description of the infrastructure for Bayesian spatial proteomics, please see
Crook OM, Mulvey CM, Kirk PDW, Lilley KS, Gatto L (2018) A Bayesian mixture modelling approach for spatial proteomics. PLoS Comput Biol 14(11): e1006516. https://doi.org/10.1371/journal.pcbi.1006516
For a detailed application of the method, please see
Oliver M. Crook, Lisa M. Breckels, Kathryn S. Lilley, Paul D.W. Kirk, Laurent Gatto. A Bioconductor workflow for the Bayesian analysis of spatial proteomics [version 1; peer review: awaiting peer review]. F1000Research 2019, 8:446 https://doi.org/10.12688/f1000research.18636.1.