False discovery rates and related statistical concepts in mass spectrometry-based proteomics

被引：165

作者：

Choi, Hyungwon ^{[1
,2
]}

Nesvizhskii, Alexey I. ^{[1
,3
]}

机构：

[1] Univ Michigan, Dept Pathol, Ann Arbor, MI 48109 USA

[2] Univ Michigan, Dept Biostat, Ann Arbor, MI 48109 USA

[3] Univ Michigan, Ctr Comp Med & Biol, Ann Arbor, MI 48109 USA

来源：

JOURNAL OF PROTEOME RESEARCH | 2008年 / 7卷 / 01期

关键词：

mass spectrometry; peptide identification; database searching; statistical validation; decoy sequences; false discovery rates;

D O I：

10.1021/pr700747q

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Development of statistical methods for assessing the significance of peptide assignments to tandem mass spectra obtained using database searching remains an important problem. In the past several years, several different approaches have emerged, including the concept of expectation values, target-decoy strategy, and the probability mixture modeling approach of PeptideProphet. In this work, we provide a background on statistical significance analysis in the field of mass spectrometry-based proteomics, and present our perspective on the current and future developments in this area.

引用

页码：47 / 50

页数：4

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