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. Cross-linking 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 cross-links 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, gene ontology (GO) enrichment,
post-translational modification (PTM) visualization, domains and secondary
structure mapping, data set comparison, previsualization overlap check,
and more. Validation of detected cross-links is available for proteins
and complexes with known structure or for protein complexes through
the DisVis online platform (
). Graphs are exportable in PDF format, and data sets can be exported
in tab-separated text files for evaluation through other software.