Interactive Chord Visualization for Metaproteomics

Abstract

Metaproteomics is an analytic approach to research microorganisms that live in complex microbial communities. A key aspect of understanding microbial communities is to link the functions of proteins identified by metaproteomics to their taxonomy. In this paper we demonstrate the interactive chord visualization as a powerful tool to explore such data. To evaluate the tools efficacy, we use the relation data between functions and taxonomies from a large metaproteomics experiment. We evaluated the work flow in comparison to previous methods of data analysis and showed that interactive exploration of data using the chord diagram is significantly faster in four of five tasks. Therefore, the chord visualization improves the user's ability to discover complex biological relationships.