In shotgun proteomics, false discovery
rate (FDR) estimation is
a necessary step to ensure the quality of accepted peptide-spectrum
matches (PSMs) from a database search. Popular statistical validation
tools for FDR control tend to rely on target-decoy searching to build
empirical, dataset-specific models, which often leads to inaccurate
FDR estimates. In this paper, we propose a new approach named common
decoy distribution (CDD) to FDR estimation using the idea of a fixed
empirical null score distribution derived from millions of peptide
tandem mass spectra. To demonstrate the viability of CDD, its stability
with respect to noise and the presence of unexpected peptide modifications
was evaluated. PeptideProphet-based implementation of CDD was benchmarked
against decoy-based PeptideProphet, and both methods exhibited similar
accuracy of FDR estimates and retrieval of correct PSMs. The finding
of this study calls for a re-evaluation of the necessity of dataset-specific
target-decoy searches and illustrates the potential of Big Data approaches
for statistical analysis in proteomics.
The formation of covalently bound DNA−protein crosslinks (DPCs) is linked to the pathophysiology of cancers and many other degenerative diseases. Knowledge of the proteins that were frequently involved in forming DPCs will improve our understanding of the etiological mechanism of diseases and facilitate the establishment of preventive measures and treatment methods. By using SDS-PAGE and nano-LC coupled Orbitrap LC-MS/MS analyses, we identified, for the first time, that the major DNA-cross-linked proteins in HeLa cells exposed to a methylating agent (methylmethanesulfonate) or hydroxyl free radicals are transcription-associated proteins. In particular, histone H2B3B and poly(rC) binding protein 2 were identified as the most frequent DPC-forming proteins.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.