Metaproteomics is a maturing research discipline that can be used to look at the protein contents of samples taken from environments such as the human gut, soil, or sludge. Based on protein fragments (peptides) found in the samples, we can try to infer which proteins the peptides originate from, which (micro)organisms created them and what functions they perform. This way, we can gain insight into the processes that take place in ecosystems, find out about disruptions and discover potential solutions to resolve imbalances.

Unfortunately, the available software to analyse this wealth of data is clearly lagging behind the technical advances in the field. To remedy this, we developed Unipept, a user-friendly web application that enables researchers to easily explore their data using interactive data visualisations. Originally, we were primarily interested in sample biodiversity, but recently we have shifted our focus to the functional composition and the link between organisms and functions.

The analyses in Unipept are done on a per-sample basis, but to get the most out of the data, it is necessary to be able to compare multiple samples and detect shifts in composition. This research proposal aims to add such comparative analysis to Unipept in an easy to use, but statistically-correct way. This will make it possible to, for example, compare healthy with diseased patients or to track the effectiveness of an intervention.