title: An optimized data structure for high-throughput 3D proteomics data: mzRTree.
abstract: As an emerging field, MS-based proteomics still requires software tools for efficiently storing and accessing experimental data. In this work, we focus on the management of LC-MS data, which are typically made available in standard XML-based portable formats. The structures that are currently employed to manage these data can be highly inefficient, especially when dealing with high-throughput profile data. LC-MS datasets are usually accessed through 2D range queries. Optimizing this type of operation could dramatically reduce the complexity of data analysis. We propose a novel data structure for LC-MS datasets, called mzRTree, which embodies a scalable index based on the R-tree data structure. mzRTree can be efficiently created from the XML-based data formats and it is suitable for handling very large datasets. We experimentally show that, on all range queries, mzRTree outperforms other known structures used for LC-MS data, even on those queries these structures are optimized for. Besides, mzRTree is also more space efficient. As a result, mzRTree reduces data analysis computational costs for very large profile datasets.
authors.affiliation: Department of Information Engineering, University of Padova, Padova Italy. sara.nasso@dei.unipd.it
authors.forename: Sara
authors.initials: S
authors.lastname: Nasso
authors.forename: Francesco
authors.initials: F
authors.lastname: Silvestri
authors.forename: Francesco
authors.initials: F
authors.lastname: Tisiot
authors.forename: Barbara
authors.initials: B
authors.lastname: Di Camillo
authors.forename: Andrea
authors.initials: A
authors.lastname: Pietracaprina
authors.forename: Gianna Maria
authors.initials: GM
authors.lastname: Toffolo
mesh_terms: D000465:Algorithms; D002853:Chromatography, Liquid / Q000379:methods; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D021621:Imaging, Three-Dimensional; D013058:Mass Spectrometry / Q000379:methods; D011381:Programming Languages; D020543:Proteome; D040901:Proteomics / Q000379:methods*; D015203:Reproducibility of Results; D012984:Software; D013997:Time Factors
chemical_list: D020543:Proteome