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- Title
libfbi: a C++ implementation for fast box intersection and application to sparse mass spectrometry data.
- Authors
Kirchner, Marc; Xu, Buote; Steen, Hanno; Steen, Judith A. J.
- Abstract
Motivation: Algorithms for sparse data require fast search and subset selection capabilities for the determination of point neighborhoods. A natural data representation for such cases are space partitioning data structures. However, the associated range queries assume noise-free observations and cannot take into account observation-specific uncertainty estimates that are present in e.g. modern mass spectrometry data. In order to accommodate the inhomogeneous noise characteristics of sparse real-world datasets, point queries need to be reformulated in terms of box intersection queries, where box sizes correspond to uncertainty regions for each observation.Results: This contribution introduces libfbi, a standard C++, header-only template implementation for fast box intersection in an arbitrary number of dimensions, with arbitrary data types in each dimension. The implementation is applied to a data aggregation task on state-of-the-art liquid chromatography/mass spectrometry data, where it shows excellent run time properties.Availability: The library is available under an MIT license and can be downloaded from http://software.steenlab.org/libfbi.Contact: marc.kirchner@childrens.harvard.eduSupplementary information: Supplementary data are available at Bioinformatics online.
- Subjects
C++; MASS spectrometry; COMPUTER algorithms; SEARCH engines; DATA mining; LIQUID chromatography; BIOINFORMATICS
- Publication
Bioinformatics, 2011, Vol 27, Issue 8, p1166
- ISSN
1367-4803
- Publication type
Article
- DOI
10.1093/bioinformatics/btr084