PhosR enables processing and functional analysis of phosphoproteomic data

Mass spectrometry-based phosphoproteomics has transformed our ability to profile phosphorylation-based signalling in tissues and cells on a global scale. To infer the action of kinases and signalling pathways in phosphoproteomic experiments, we present PhosR, a set of tools and methodologies implemented in a suite of R packages for the comprehensive analysis of phosphoproteomic data. By applying to both published and new phosphoproteomic datasets, we illustrate PhosR in data imputation and normalisation using a novel set of ‘stably phosphorylated sites’ and in functional analysis for inferring kinase activities and signalling pathways. In particular, we introduce a ‘signalome’ construction method for identifying a collection of signalling modules that allow us to summarise and visualise the interaction of kinases and their collective action on signal transduction. Together, our data and findings demonstrate the utility of PhosR in processing and generating novel biological knowledge from MS-based phosphoproteomic data.