title: Analysis of iTRAQ data using Mascot and Peaks quantification algorithms.
abstract: The field of proteomics has been developing rapidly toward quantification of proteins. Despite the variety of experimental techniques available for peptide and protein labelling, there are few commercially available analytical tools with the ability to interpret data from any mass spectrometer. In this study, we compare two software packages, Mascot and Peaks, for the analysis of iTRAQ data from ESI-Q/TOF mass spectrometry. In the case of a six-protein mixture combined in a known proportion, the output of the Peaks algorithm deviated from the correct result by 14% on average, while the error of the Mascot quantification was nearly 200%. When the software were used to analyse iTRAQ data from a complex protein sample, the quantification results agreed within 20% for only 26% of the quantified proteins, showing significant differences in the two quantification algorithms. This comparison and analysis revealed major intricacies in peptide and protein quantification that must be taken into consideration for software development.
authors.affiliation: Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, CO 80523, USA.
authors.forename: Carla M R
authors.initials: CM
authors.lastname: Lacerda
authors.forename: Lei
authors.initials: L
authors.lastname: Xin
authors.forename: Iain
authors.initials: I
authors.lastname: Rogers
authors.forename: Kenneth F
authors.initials: KF
authors.lastname: Reardon
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000818:Animals; D002417:Cattle; D002645:Chickens; D006801:Humans; D008969:Molecular Sequence Data; D011506:Proteins / Q000737:chemistry / Q000378:metabolism; D012984:Software; D053719:Tandem Mass Spectrometry / Q000379:methods*
chemical_list: D011506:Proteins