STEPS: a grid search methodology for optimized peptide identification filtering of MS/MS database search results.
Proteomics
; 13(5): 766-70, 2013 Mar.
Article
em En
| MEDLINE
| ID: mdl-23303698
ABSTRACT
For bottom-up proteomics, there are wide variety of database-searching algorithms in use for matching peptide sequences to tandem MS spectra. Likewise, there are numerous strategies being employed to produce a confident list of peptide identifications from the different search algorithm outputs. Here we introduce a grid-search approach for determining optimal database filtering criteria in shotgun proteomics data analyses that is easily adaptable to any search. Systematic Trial and Error Parameter Selection--referred to as STEPS--utilizes user-defined parameter ranges to test a wide array of parameter combinations to arrive at an optimal "parameter set" for data filtering, thus maximizing confident identifications. The benefits of this approach in terms of numbers of true-positive identifications are demonstrated using datasets derived from immunoaffinity-depleted blood serum and a bacterial cell lysate, two common proteomics sample types.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Fragmentos de Peptídeos
/
Proteínas
/
Bases de Dados de Proteínas
/
Proteômica
/
Espectrometria de Massas em Tandem
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2013
Tipo de documento:
Article