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Improved False Discovery Rate Estimation Procedure for Shotgun Proteomics
被引:44
|作者:
Keich, Uri
[1
]
Kertesz-Farkas, Attila
[2
]
Noble, William Stafford
[2
,3
]
机构:
[1] Univ Sydney, Sch Math & Stat F07, Sydney, NSW 2006, Australia
[2] Univ Washington, Dept Genome Sci, Seattle, WA 98195 USA
[3] Univ Washington, Dept Comp Sci & Engn, Seattle, WA 98195 USA
关键词:
mass spectrometry;
spectrum identification;
false discovery rate;
DECOY SEARCH STRATEGY;
TANDEM MASS-SPECTRA;
PEPTIDE IDENTIFICATION;
SPECTROMETRY;
PROBABILITIES;
DATABASES;
VALUES;
D O I:
10.1021/acs.jproteome.5b00081
中图分类号:
Q5 [生物化学];
学科分类号:
071010 ;
081704 ;
摘要:
Interpreting the potentially vast number of hypotheses generated by a shotgun proteomics experiment requires a valid and accurate procedure for assigning statistical confidence estimates to identified tandem mass spectra. Despite the crucial role such procedures play in most high-throughput proteomics experiments, the scientific literature has not reached a consensus about the best confidence estimation methodology. In this work, we evaluate, using theoretical and empirical analysis, four previously proposed protocols for estimating the false discovery rate (FDR) associated with a set of identified tandem mass spectra: two variants of the target-decoy competition protocol (TDC) of Elias and Gygi and two variants of the separate target-decoy search protocol of Kall et al. Our analysis reveals significant biases in the two separate target-decoy search protocols. Moreover, the one TDC protocol that provides an unbiased FDR estimate among the target PSMs does so at the cost of forfeiting a random subset of high-scoring spectrum identifications. We therefore propose the mix-max procedure to provide unbiased, accurate FDR estimates in the presence of well-calibrated scores. The method avoids biases associated with the two separate target-decoy search protocols and also avoids the propensity for target-decoy competition to discard a random subset of high-scoring target identifications.
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页码:3148 / 3161
页数:14
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