Nonlinear fitting method for determining local false discovery rates from decoy database searches

J Proteome Res. 2008 Sep;7(9):3661-7. doi: 10.1021/pr070492f. Epub 2008 Aug 14.


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.

MeSH terms

  • Databases, Protein*
  • Models, Theoretical
  • Nonlinear Dynamics*
  • Tandem Mass Spectrometry