False discovery rate estimation and heterobifunctional cross-linkers.

Frederique Lisacek,Lutz Fischer,Juri Rappsilber

doi:10.1371/journal.pone.0196672

Abstract

False discovery rate (FDR) estimation is a cornerstone of proteomics that has recently been adapted to cross-linking/mass spectrometry. Here we demonstrate that heterobifunctional cross-linkers, while theoretically different from homobifunctional cross-linkers, need not be considered separately in practice. We develop and then evaluate the impact of applying a correct FDR formula for use of heterobifunctional cross-linkers and conclude that there are minimal practical advantages. Hence a single formula can be applied to data generated from the many different non-cleavable cross-linkers.

Highlights

Cross-linking mass-spectrometry (CLMS) has become an increasingly popular tool for analyzing protein structures, protein networks and protein dynamics[1,2,3,4]
We provide some theoretical insights on extending the target-decoy approach to false discovery rate (FDR) estimation when using heterobifunctional cross-linkers, and assess whether it is necessary to use a different formula for FDR estimation
The error made by using formula 1 approaches zero relatively fast with increasing database size

Summary

Introduction

Cross-linking mass-spectrometry (CLMS) has become an increasingly popular tool for analyzing protein structures, protein networks and protein dynamics[1,2,3,4]. The question of what is the correct error estimation to use with CLMS has been addressed with the help of a target-decoy database approach[5], based on previous work for cross-linked[6,7] and linear peptides[8,9,10,11]. We provide some theoretical insights on extending the target-decoy approach to FDR estimation when using heterobifunctional cross-linkers, and assess whether it is necessary to use a different formula for FDR estimation.

Results

Conclusion