Assessment of Reported Error Rates in Crosslinking Mass Spectrometry
We benchmarked eight software tools in crosslinking mass spectrometry (MS) to evaluate their accuracy in detecting protein-protein interactions. Whereas about half performed reliably, others reported up to 31-fold more false interactions than indicated by their reported false discovery rates. During this community-driven effort, we helped correct one of the poorer-performing tools. Our findings demonstrate that, with robust algorithms, crosslinking MS can deliver highly dependable insights into biological systems.
bioinformatics↗