Analytical Chemistry · 2017 · 191 citations · 22 references
Life SciencesBiochemistryBioinformaticsMass Spectrometric AnalysisProteomicsStructural BiologyMass SpectrometryMass Spectrometry Data AnalysisPeptide AnalysisPeptide IdentificationProtein IdentificationStructural ProteomicsAccuracyCross-linking Mass SpectrometryEstimation ErrorFalse Detection RatesFalse Discovery RatePeptide False Discovery Rate EstimationPeptide-spectrum MatchingPrediction Error Assessment
Cross‑linking/mass spectrometry is increasingly used to obtain structural information on proteins and complexes, but reliable error‑assessment methods are still under development. The study introduces xiFDR, an open‑source tool designed to apply these error‑estimation observations routinely. xiFDR estimates false‑discovery rates at critical analysis stages, applies prefiltering of peptide‑spectrum matches and peptide pairs to improve results, and makes the data available via ProteomeXchange (PXD004749). Correcting the FDR estimation point lowered the error from 8.4% to the targeted 5%, and prefiltering increased residue‑pair counts by 33% (108→144) at 5% FDR while maintaining accuracy, as the added data agreed with the crystal structure.
Cross-linking/mass spectrometry is an increasingly popular approach to obtain structural information on proteins and their complexes in solution. However, methods for error assessment are under current development. We note that false-discovery rates can be estimated at different points during data analysis, and are most relevant for residue or protein pairs. Missing this point led in our example analysis to an actual 8.4% error when 5% error was targeted. In addition, prefiltering of peptide-spectrum matches and of identified peptide pairs substantially improved results. In our example, this prefiltering increased the number of residue pairs (5% FDR) by 33% (n = 108 to n = 144). This number improvement did not come at the expense of reduced accuracy as the added data agreed with an available crystal structure. We provide an open-source tool, xiFDR ( https://github.com/rappsilberlab/xiFDR ), that implements our observations for routine application. Data are available via ProteomeXchange with identifier PXD004749.
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2016 update of the PRIDE database and its related tools
Juan Antonio Vizcaíno, Attila Csordás, Noemí del‐Toro et al. · Nucleic Acids Research · 2015 · 3.7K citations · Full text
Proteome-wide profiling of protein assemblies by cross-linking mass spectrometry
Fan Liu, Dirk T. S. Rijkers, Harm Post et al. · Nature Methods · 2015 · 498 citations · Full text