title: Nonlinear fitting method for determining local false discovery rates from decoy database searches.
abstract: False discovery rate (FDR) analyses of protein and peptide identification results using decoy database searching conventionally report aggregate or global FDRs for a whole set of identifications, which are often not very informative about the error rates of individual members in the set. We describe a nonlinear curve fitting method for calculating the local FDR, which estimates the chance that an individual protein (or peptide) is incorrect, and present a simple tool that implements this analysis. The goal of this method is to offer a simple extension to the now commonplace decoy database searching, providing additional valuable information.
authors.affiliation: Applied Biosystems | MDS Analytical Technologies, Foster City, CA 94404, USA.
authors.forename: Wilfred H
authors.initials: WH
authors.lastname: Tang
authors.forename: Ignat V
authors.initials: IV
authors.lastname: Shilov
authors.forename: Sean L
authors.initials: SL
authors.lastname: Seymour
mesh_terms: D030562:Databases, Protein; D008962:Models, Theoretical; D017711:Nonlinear Dynamics; D053719:Tandem Mass Spectrometry