title: Peptizer, a tool for assessing false positive peptide identifications and manually validating selected results.
abstract: False positive peptide identifications are a major concern in the field of peptidecentric, mass spectrometry-driven gel-free proteomics. They occur in regions where the score distributions of true positives and true negatives overlap. Removal of these false positive identifications necessarily involves a trade-off between sensitivity and specificity. Existing postprocessing tools typically rely on a fixed or semifixed set of assumptions in their attempts to optimize both the sensitivity and the specificity of peptide and protein identification using MS/MS spectra. Because of the expanding diversity in available proteomics technologies, however, these postprocessing tools often struggle to adapt to emerging technology-specific peculiarity. Here we present a novel tool named Peptizer that solves this adaptability issue by making use of pluggable assumptions. This research-oriented postprocessing tool also includes a graphical user interface to perform efficient manual validation of suspect identifications for optimal sensitivity recovery. Peptizer is open source software under the Apache2 license and is written in Java.
authors.affiliation: Department of Medical Protein Research, VIB, B-9000 Ghent, Belgium.
authors.forename: Kenny
authors.initials: K
authors.lastname: Helsens
authors.forename: Evy
authors.initials: E
authors.lastname: Timmerman
authors.forename: Joël
authors.initials: J
authors.lastname: Vandekerckhove
authors.forename: Kris
authors.initials: K
authors.lastname: Gevaert
authors.forename: Lennart
authors.initials: L
authors.lastname: Martens
mesh_terms: D001331:Automation; D005189:False Positive Reactions; D006801:Humans; D020014:K562 Cells; D010455:Peptides / Q000032:analysis*; D040901:Proteomics / Q000379:methods*; D015203:Reproducibility of Results; D012984:Software; D014584:User-Computer Interface
chemical_list: D010455:Peptides