title: On the estimation of false positives in peptide identifications using decoy search strategy.
abstract: False positive control/estimate in peptide identifications by MS is of critical importance for reliable inference at the protein level and downstream bioinformatics analysis. Approaches based on search against decoy databases have become popular for its conceptual simplicity and easy implementation. Although various decoy search strategies have been proposed, few studies have investigated their difference in performance. With datasets collected on a mixture of model proteins, we demonstrate that a single search against the target database coupled with its reversed version offers a good balance between performance and simplicity. In particular, both the accuracy of the estimate of the number of false positives and sensitivity is at least comparable to other procedures examined in this study. It is also shown that scrambling while preserving frequency of amino acid words can potentially improve the accuracy of false positive estimate, though more studies are needed to investigate the optimal scrambling procedure for specific condition and the variation of the estimate across repeated scrambling.
authors.affiliation: Division of Biostatistics, Indiana University School of Medicine, Indianapolis, IN 46202 , USA. chashen@iupui.edu
authors.forename: Changyu
authors.initials: C
authors.lastname: Shen
authors.forename: Quanhu
authors.initials: Q
authors.lastname: Sheng
authors.forename: Jie
authors.initials: J
authors.lastname: Dai
authors.forename: Yixue
authors.initials: Y
authors.lastname: Li
authors.forename: Rong
authors.initials: R
authors.lastname: Zeng
authors.forename: Haixu
authors.initials: H
authors.lastname: Tang
mesh_terms: D030562:Databases, Protein; D013058:Mass Spectrometry; D015233:Models, Statistical; D010455:Peptides / Q000032:analysis*; D012680:Sensitivity and Specificity; D020539:Sequence Analysis, Protein / Q000379:methods*
chemical_list: D010455:Peptides