Cross-ID: Analysis and Visualization of Complex XL-MS Driven Protein Interaction Networks

Abstract

Protein interactions enable much more complex behavior than the sum of the individual protein parts would suggest and represents a level of biological complexity requiring full understanding when unravelling cellular processes. Crosslinking mass spectrometry has emerged as an attractive approach to study these interactions and recent advances in mass spectrometry and data analysis software have enabled the identification of thousands of crosslinks from a single experiment. The resulting data complexity is however difficult to understand and requires interactive software tools. Even though solutions are available, these represent an agglomerate of possibilities and each features its own input format often forcing manual conversion. Here we present Cross-ID, a visualization platform that links directly into the output of XlinkX for Proteome Discoverer, but also plays well with other platforms by supporting a user-controllable text-file importer. The platform includes features like grouping, spectral viewer, GO enrichment, PTM-visualization, domain- and secondary structure mapping, dataset comparison, pre-visualization overlap-check and more. Validation of detected crosslinks is available for proteins and complexes with known structure or for protein complexes through the DisVis online platform (http://milou.science.uu.nl/cgi/services/DISVIS/disvis/). Graphs are exportable in PDF format, and datasets can be exported in tab separated text files for evaluation through other software.