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Dinosaur: A Refined Open-Source Peptide MS Feature Detector

[Image: see text] 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 complex...

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Autores principales: Teleman, Johan, Chawade, Aakash, Sandin, Marianne, Levander, Fredrik, Malmström, Johan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2016
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4933939/
https://www.ncbi.nlm.nih.gov/pubmed/27224449
http://dx.doi.org/10.1021/acs.jproteome.6b00016
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author Teleman, Johan
Chawade, Aakash
Sandin, Marianne
Levander, Fredrik
Malmström, Johan
author_facet Teleman, Johan
Chawade, Aakash
Sandin, Marianne
Levander, Fredrik
Malmström, Johan
author_sort Teleman, Johan
collection PubMed
description [Image: see text] 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.
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spelling pubmed-49339392016-07-07 Dinosaur: A Refined Open-Source Peptide MS Feature Detector Teleman, Johan Chawade, Aakash Sandin, Marianne Levander, Fredrik Malmström, Johan J Proteome Res [Image: see text] 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. American Chemical Society 2016-05-25 2016-07-01 /pmc/articles/PMC4933939/ /pubmed/27224449 http://dx.doi.org/10.1021/acs.jproteome.6b00016 Text en Copyright © 2016 American Chemical Society This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes.
spellingShingle Teleman, Johan
Chawade, Aakash
Sandin, Marianne
Levander, Fredrik
Malmström, Johan
Dinosaur: A Refined Open-Source Peptide MS Feature Detector
title Dinosaur: A Refined Open-Source Peptide MS Feature Detector
title_full Dinosaur: A Refined Open-Source Peptide MS Feature Detector
title_fullStr Dinosaur: A Refined Open-Source Peptide MS Feature Detector
title_full_unstemmed Dinosaur: A Refined Open-Source Peptide MS Feature Detector
title_short Dinosaur: A Refined Open-Source Peptide MS Feature Detector
title_sort dinosaur: a refined open-source peptide ms feature detector
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4933939/
https://www.ncbi.nlm.nih.gov/pubmed/27224449
http://dx.doi.org/10.1021/acs.jproteome.6b00016
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