Learning from decoys to improve the sensitivity and specificity of proteomics database search results.

ABSTRACT: The statistical validation of database search results is a complex issue in bottom-up proteomics. The correct and incorrect peptide spectrum match (PSM) scores overlap significantly, making an accurate assessment of true peptide matches challenging. Since the complete separation between the true and false hits is practically never achieved, there is need for better methods and rescoring algorithms to improve upon the primary database search results. Here we describe the calibration and False Discovery Rate (FDR) estimation of database search scores through a dynamic FDR calculation method, FlexiFDR, which increases both the sensitivity and specificity of search results. Modelling a simple linear regression on the decoy hits for different charge states, the method maximized the number of tr

SUBMITTER: Yadav AK 

PROVIDER: S-EPMC3506577 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature