title: A non-parametric cutout index for robust evaluation of identified proteins.
abstract: This paper proposes a novel, automated method for evaluating sets of proteins identified using mass spectrometry. The remaining peptide-spectrum match score distributions of protein sets are compared to an empirical absent peptide-spectrum match score distribution, and a Bayesian non-parametric method reminiscent of the Dirichlet process is presented to accurately perform this comparison. Thus, for a given protein set, the process computes the likelihood that the proteins identified are correctly identified. First, the method is used to evaluate protein sets chosen using different protein-level false discovery rate (FDR) thresholds, assigning each protein set a likelihood. The protein set assigned the highest likelihood is used to choose a non-arbitrary protein-level FDR threshold. Because the method can be used to evaluate any protein identification strategy (and is not limited to mere comparisons of different FDR thresholds), we subsequently use the method to compare and evaluate multiple simple methods for merging peptide evidence over replicate experiments. The general statistical approach can be applied to other types of data (e.g. RNA sequencing) and generalizes to multivariate problems.
authors.affiliation: Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
authors.forename: Oliver
authors.initials: O
authors.lastname: Serang
authors.forename: Joao
authors.initials: J
authors.lastname: Paulo
authors.forename: Hanno
authors.initials: H
authors.lastname: Steen
authors.forename: Judith A
authors.initials: JA
authors.lastname: Steen
mesh_terms: D001499:Bayes Theorem; D006367:HeLa Cells; D006801:Humans; D013058:Mass Spectrometry / Q000379:methods*; D015233:Models, Statistical; D010455:Peptides / Q000032:analysis / Q000737:chemistry; D011336:Probability; D011506:Proteins / Q000032:analysis* / Q000737:chemistry; D040901:Proteomics / Q000379:methods; D015203:Reproducibility of Results; D018709:Statistics, Nonparametric
chemical_list: D010455:Peptides; D011506:Proteins