Verification of single-peptide protein identifications by the application of complementary database search algorithms.
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.
Rohrbough
James G
JG
Department of Biochemistry and Molecular Biophysics, The University of Arizona, Tucson, USA.
Breci
Linda
L
Merchant
Nirav
N
Miller
Susan
S
Haynes
Paul A
PA
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
D010455:Peptides; D010940:Plant Proteins; D011506:Proteins