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Efficient Genomic Interval Queries Using Augmented Range Trees

Efficient large-scale annotation of genomic intervals is essential for personal genome interpretation in the realm of precision medicine. There are 13 possible relations between two intervals according to Allen’s interval algebra. Conventional interval trees are routinely used to identify the genomi...

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Autores principales: Mao, Chengsheng, Eran, Alal, Luo, Yuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6434014/
https://www.ncbi.nlm.nih.gov/pubmed/30911095
http://dx.doi.org/10.1038/s41598-019-41451-3
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author Mao, Chengsheng
Eran, Alal
Luo, Yuan
author_facet Mao, Chengsheng
Eran, Alal
Luo, Yuan
author_sort Mao, Chengsheng
collection PubMed
description Efficient large-scale annotation of genomic intervals is essential for personal genome interpretation in the realm of precision medicine. There are 13 possible relations between two intervals according to Allen’s interval algebra. Conventional interval trees are routinely used to identify the genomic intervals satisfying a coarse relation with a query interval, but cannot support efficient query for more refined relations such as all Allen’s relations. We design and implement a novel approach to address this unmet need. Through rewriting Allen’s interval relations, we transform an interval query to a range query, then adapt and utilize the range trees for querying. We implement two types of range trees: a basic 2-dimensional range tree (2D-RT) and an augmented range tree with fractional cascading (RTFC) and compare them with the conventional interval tree (IT). Theoretical analysis shows that RTFC can achieve the best time complexity for interval queries regarding all Allen’s relations among the three trees. We also perform comparative experiments on the efficiency of RTFC, 2D-RT and IT in querying noncoding element annotations in a large collection of personal genomes. Our experimental results show that 2D-RT is more efficient than IT for interval queries regarding most of Allen’s relations, RTFC is even more efficient than 2D-RT. The results demonstrate that RTFC is an efficient data structure for querying large-scale datasets regarding Allen’s relations between genomic intervals, such as those required by interpreting genome-wide variation in large populations.
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spelling pubmed-64340142019-04-02 Efficient Genomic Interval Queries Using Augmented Range Trees Mao, Chengsheng Eran, Alal Luo, Yuan Sci Rep Article Efficient large-scale annotation of genomic intervals is essential for personal genome interpretation in the realm of precision medicine. There are 13 possible relations between two intervals according to Allen’s interval algebra. Conventional interval trees are routinely used to identify the genomic intervals satisfying a coarse relation with a query interval, but cannot support efficient query for more refined relations such as all Allen’s relations. We design and implement a novel approach to address this unmet need. Through rewriting Allen’s interval relations, we transform an interval query to a range query, then adapt and utilize the range trees for querying. We implement two types of range trees: a basic 2-dimensional range tree (2D-RT) and an augmented range tree with fractional cascading (RTFC) and compare them with the conventional interval tree (IT). Theoretical analysis shows that RTFC can achieve the best time complexity for interval queries regarding all Allen’s relations among the three trees. We also perform comparative experiments on the efficiency of RTFC, 2D-RT and IT in querying noncoding element annotations in a large collection of personal genomes. Our experimental results show that 2D-RT is more efficient than IT for interval queries regarding most of Allen’s relations, RTFC is even more efficient than 2D-RT. The results demonstrate that RTFC is an efficient data structure for querying large-scale datasets regarding Allen’s relations between genomic intervals, such as those required by interpreting genome-wide variation in large populations. Nature Publishing Group UK 2019-03-25 /pmc/articles/PMC6434014/ /pubmed/30911095 http://dx.doi.org/10.1038/s41598-019-41451-3 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Mao, Chengsheng
Eran, Alal
Luo, Yuan
Efficient Genomic Interval Queries Using Augmented Range Trees
title Efficient Genomic Interval Queries Using Augmented Range Trees
title_full Efficient Genomic Interval Queries Using Augmented Range Trees
title_fullStr Efficient Genomic Interval Queries Using Augmented Range Trees
title_full_unstemmed Efficient Genomic Interval Queries Using Augmented Range Trees
title_short Efficient Genomic Interval Queries Using Augmented Range Trees
title_sort efficient genomic interval queries using augmented range trees
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6434014/
https://www.ncbi.nlm.nih.gov/pubmed/30911095
http://dx.doi.org/10.1038/s41598-019-41451-3
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