Search engine processor: Filtering and organizing peptide spectrum matches

被引：101

作者：

Carvalho, Paulo C. ^{[1
,2
]}

Fischer, Juliana S. G. ^{[1
,2
]}

Xu, Tao ^{[3
]}

Cociorva, Daniel ^{[3
]}

Balbuena, Tiago S. ^{[4
]}

Valente, Richard H. ^{[2
]}

Perales, Jonas ^{[2
]}

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

Barbosa, Valmir C. ^{[5
]}

机构：

[1] Fiocruz MS, Carlos Chagas Inst, BR-81350010 Curitiba, Parana, Brazil

[2] Inst Oswaldo Cruz, Lab Toxinol, BR-20001 Rio De Janeiro, Brazil

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

[4] Univ Missouri, Dept Biochem, Columbia, MO USA

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

来源：

PROTEOMICS | 2012年 / 12卷 / 07期

基金：

美国国家卫生研究院;

关键词：

Bioinformatics; Filtering; Quality; Semi-labeled decoy approach; Sharing; Shotgun proteomics; TANDEM MASS-SPECTROMETRY; STATISTICAL-MODEL; GENE-ONTOLOGY; IDENTIFICATION; PROTEOMICS; TOOL; PROTEINS; MS/MS;

D O I：

10.1002/pmic.201100529

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

The search engine processor (SEPro) is a tool for filtering, organizing, sharing, and displaying peptide spectrum matches. It employs a novel three-tier Bayesian approach that uses layers of spectrum, peptide, and protein logic to lead the data to converge to a single list of reliable protein identifications. SEPro is integrated into the PatternLab for proteomics environment, where an arsenal of tools for analyzing shotgun proteomic data is provided. By using the semi-labeled decoy approach for benchmarking, we show that SEPro significantly outperforms a commercially available competitor.

引用

页码：944 / 949

页数：6

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