Granholm V, Navarro JF, Noble WS, Käll L
J Proteomics 80 (-) 123-131 [2013-03-27; online 2012-12-23]
The analysis of a shotgun proteomics experiment results in a list of peptide-spectrum matches (PSMs) in which each fragmentation spectrum has been matched to a peptide in a database. Subsequently, most protein inference algorithms rank peptides according to the best-scoring PSM for each peptide. However, there is disagreement in the scientific literature on the best method to assess the statistical significance of the resulting peptide identifications. Here, we use a previously described calibration protocol to evaluate the accuracy of three different peptide-level statistical confidence estimation procedures: the classical Fisher's method, and two complementary procedures that estimate significance, respectively, before and after selecting the top-scoring PSM for each spectrum. Our experiments show that the latter method, which is employed by MaxQuant and Percolator, produces the most accurate, well-calibrated results.