Can the false-discovery rate be misleading?

被引：35

作者：

Barboza, Rodrigo ^{[2
]}

Cociorva, Daniel ^{[3
]}

Xu, Tao ^{[3
]}

Barbosa, Valmir C. ^{[2
]}

Perales, Jonas ^{[1
]}

Valente, Richard H. ^{[1
]}

Franca, Felipe M. G. ^{[2
]}

Yates, John R., III ^{[3
]}

Carvalho, Paulo C. ^{[1
,4
]}

机构：

[1] Inst Oswaldo Cruz, Lab Toxinol, Fundacao Oswaldo Cruz FIPCRUZ, BR-21045900 Rio De Janeiro, Brazil

[2] Univ Fed Rio de Janeiro, COPPE, Syst Engn & Comp Sci Program, BR-21945 Rio De Janeiro, Brazil

[3] Scripps Res Inst, Dept Physiol Chem, La Jolla, CA 92037 USA

[4] Fundacao Oswaldo Cruz, Ctr Technol Dev Hlth, Rio De Janeiro, Brazil

来源：

PROTEOMICS | 2011年 / 11卷 / 20期

关键词：

Bioinformatics; Decoy; False-discovery rate; Overfitting; Protein identification; Shotgun proteomics; PEPTIDE IDENTIFICATION; PROTEIN;

D O I：

10.1002/pmic.201100297

中图分类号：

Q5 [生物化学];

学科分类号：

070307 [化学生物学];

摘要：

The decoy-database approach is currently the gold standard for assessing the confidence of identifications in shotgun proteomic experiments. Here, we demonstrate that what might appear to be a good result under the decoy-database approach for a given false-discovery rate could be, in fact, the product of overfitting. This problem has been overlooked until now and could lead to obtaining boosted identification numbers whose reliability does not correspond to the expected false-discovery rate. To overcome this, we are introducing a modified version of the method, termed a semi-labeled decoy approach, which enables the statistical determination of an overfitted result.

引用

页码：4105 / 4108

页数：4

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