title: Dinosaur: A Refined Open-Source Peptide MS Feature Detector.
abstract: In bottom-up mass spectrometry (MS)-based proteomics, peptide isotopic and chromatographic traces (features) are frequently used for label-free quantification in data-dependent acquisition MS but can also be used for the improved identification of chimeric spectra or sample complexity characterization. Feature detection is difficult because of the high complexity of MS proteomics data from biological samples, which frequently causes features to intermingle. In addition, existing feature detection algorithms commonly suffer from compatibility issues, long computation times, or poor performance on high-resolution data. Because of these limitations, we developed a new tool, Dinosaur, with increased speed and versatility. Dinosaur has the functionality to sample algorithm computations through quality-control plots, which we call a plot trail. From the evaluation of this plot trail, we introduce several algorithmic improvements to further improve the robustness and performance of Dinosaur, with the detection of features for 98% of MS/MS identifications in a benchmark data set, and no other algorithm tested in this study passed 96% feature detection. We finally used Dinosaur to reimplement a published workflow for peptide identification in chimeric spectra, increasing chimeric identification from 26% to 32% over the standard workflow. Dinosaur is operating-system-independent and is freely available as open source on https://github.com/fickludd/dinosaur .
authors.affiliation: Department of Immunotechnology, Lund University , 223 83 Lund, Sweden.|Department of Clinical Sciences Lund, Lund University , 221 00 Lund, Sweden.
authors.forename: Johan
authors.initials: J
authors.lastname: Teleman
authors.affiliation: Department of Immunotechnology, Lund University , 223 83 Lund, Sweden.
authors.forename: Aakash
authors.initials: A
authors.lastname: Chawade
authors.affiliation: Department of Immunotechnology, Lund University , 223 83 Lund, Sweden.
authors.forename: Marianne
authors.initials: M
authors.lastname: Sandin
authors.affiliation: Department of Immunotechnology, Lund University , 223 83 Lund, Sweden.|Bioinformatics Infrastructure for Life Sciences (BILS), Lund University , 223 83 Lund, Sweden.
authors.forename: Fredrik
authors.initials: F
authors.lastname: Levander
authors.affiliation: Department of Clinical Sciences Lund, Lund University , 221 00 Lund, Sweden.
authors.forename: Johan
authors.initials: J
authors.lastname: Malmström
mesh_terms: D000465:Algorithms; D030562:Databases, Protein; D010455:Peptides / Q000032:analysis; D040901:Proteomics / Q000379:methods*; D053719:Tandem Mass Spectrometry / Q000379:methods*; D057188:Workflow
chemical_list: D010455:Peptides
keywords: algorithm; chimeric spectra; electrospray ionization; feature detection; mass spectrometry; proteomics; software