JOURNAL ARTICLE

Empirical approach to false discovery rate estimation in shotgun proteomics

Abstract

Abstract Estimation of false discovery rate (FDR) for identified peptides is an important step in large‐scale proteomic studies. We introduced an empirical approach to the problem that is based on the FDR‐like functions of sets of peptide spectral matches (PSMs). These functions have close values for equal‐sized sets with the same FDR and depend monotonically on the FDR of a set. We have found three of them, based on three complementary sources of data: chromatography, mass spectrometry, and sequences of identified peptides. Using a calibration on a set of putative correct PSMs these functions were converted into the FDR scale. The approach was tested on a set of ∼2800 PSMs obtained from rat kidney tissue. The estimates based on all three data sources were rather consistent with each other as well as with one made using the target‐decoy strategy. Copyright © 2010 John Wiley & Sons, Ltd.

Keywords:
False discovery rate Shotgun proteomics Chemistry Set (abstract data type) Data set Computational biology Calibration Shotgun Decoy Scale (ratio) Proteomics Chromatography Data mining Computer science Statistics Artificial intelligence Mathematics Biology Biochemistry

Metrics

16
Cited By
1.70
FWCI (Field Weighted Citation Impact)
45
Refs
0.81
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Proteomics Techniques and Applications
Physical Sciences →  Chemistry →  Spectroscopy
Mass Spectrometry Techniques and Applications
Physical Sciences →  Chemistry →  Spectroscopy
Advanced Biosensing Techniques and Applications
Life Sciences →  Biochemistry, Genetics and Molecular Biology →  Molecular Biology

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