title: Mass spectrometry-based protein identification with accurate statistical significance assignment.
abstract: BACKGROUND
  Assigning statistical significance accurately has become increasingly important as metadata of many types, often assembled in hierarchies, are constructed and combined for further biological analyses. Statistical inaccuracy of metadata at any level may propagate to downstream analyses, undermining the validity of scientific conclusions thus drawn. From the perspective of mass spectrometry-based proteomics, even though accurate statistics for peptide identification can now be achieved, accurate protein level statistics remain challenging.
  
  
  RESULTS
  We have constructed a protein ID method that combines peptide evidences of a candidate protein based on a rigorous formula derived earlier; in this formula the database P-value of every peptide is weighted, prior to the final combination, according to the number of proteins it maps to. We have also shown that this protein ID method provides accurate protein level E-value, eliminating the need of using empirical post-processing methods for type-I error control. Using a known protein mixture, we find that this protein ID method, when combined with the Sorić formula, yields accurate values for the proportion of false discoveries. In terms of retrieval efficacy, the results from our method are comparable with other methods tested.
  
  
  METHODS
  The source code, implemented in C++ on a linux system, is available for download at ftp://ftp.ncbi.nlm.nih.gov/pub/qmbp/qmbp_ms/RAId/RAId_Linux_64Bit.
authors.affiliation: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA.
authors.forename: Gelio
authors.initials: G
authors.lastname: Alves
authors.affiliation: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA.
authors.forename: Yi-Kuo
authors.initials: YK
authors.lastname: Yu
mesh_terms: D000465:Algorithms; D030562:Databases, Protein; D006801:Humans; D013058:Mass Spectrometry / Q000379:methods*; D015233:Models, Statistical; D010446:Peptide Fragments / Q000032:analysis*; D011506:Proteins / Q000032:analysis* / Q000378:metabolism; D040901:Proteomics / Q000379:methods*
chemical_list: D010446:Peptide Fragments; D011506:Proteins