title: Verification of single-peptide protein identifications by the application of complementary database search algorithms.
abstract: Data produced from the MudPIT analysis of yeast (S. cerevisiae) and rice (O. sativa) were used to develop a technique to validate single-peptide protein identifications using complementary database search algorithms. This results in a considerable reduction of overall false-positive rates for protein identifications; the overall false discovery rates in yeast are reduced from near 25% to less than 1%, and the false discovery rate of yeast single-peptide protein identifications becomes negligible. This technique can be employed by laboratories utilizing a SEQUEST-based proteomic analysis platform, incorporating the XTandem algorithm as a complementary tool for verification of single-peptide protein identifications. We have achieved this using open-source software, including several data-manipulation software tools developed in our laboratory, which are freely available to download.
authors.affiliation: Department of Biochemistry and Molecular Biophysics, The University of Arizona, Tucson, USA.
authors.forename: James G
authors.initials: JG
authors.lastname: Rohrbough
authors.forename: Linda
authors.initials: L
authors.lastname: Breci
authors.forename: Nirav
authors.initials: N
authors.lastname: Merchant
authors.forename: Susan
authors.initials: S
authors.lastname: Miller
authors.forename: Paul A
authors.initials: PA
authors.lastname: Haynes
mesh_terms: D000465:Algorithms; D030562:Databases, Protein; D012275:Oryza / Q000737:chemistry; D010455:Peptides / Q000032:analysis* / Q000737:chemistry; D010940:Plant Proteins / Q000032:analysis / Q000737:chemistry; D011506:Proteins / Q000032:analysis* / Q000737:chemistry
chemical_list: D010455:Peptides; D010940:Plant Proteins; D011506:Proteins