Loading [a11y]/accessibility-menu.js
An Efficient Search Algorithm for Finding Genomic-Range Overlaps Based on the Maximum Range Length | IEEE Journals & Magazine | IEEE Xplore

An Efficient Search Algorithm for Finding Genomic-Range Overlaps Based on the Maximum Range Length


Abstract:

Efficient search algorithms for finding genomic-range overlaps are essential for various bioinformatics applications. A majority of fast algorithms for searching the over...Show More

Abstract:

Efficient search algorithms for finding genomic-range overlaps are essential for various bioinformatics applications. A majority of fast algorithms for searching the overlaps between a query range (e.g., a genomic variant) and a set of N reference ranges (e.g., exons) has time complexity of O(k + logN), where k denotes a term related to the length and location of the reference ranges. Here, we present a simple but efficient algorithm that reduces k, based on the maximum reference range length. Specifically, for a given query range and the maximum reference range length, the proposed method divides the reference range set into three subsets: always, potentially , and never overlapping. Therefore, search effort can be reduced by excluding never overlapping subset. We demonstrate that the running time of the proposed algorithm is proportional to potentially overlapping subset size, that is proportional to the maximum reference range length if all the other conditions are the same. Moreover, an implementation of our algorithm was 13.8 to 30.0 percent faster than one of the fastest range search methods available when tested on various genomic-range data sets. The proposed algorithm has been incorporated into a disease-linked variant prioritization pipeline for WGS (http://gnome.tchlab.org) and its implementation is available at http://ml.ssu.ac.kr/gSearch.
Published in: IEEE/ACM Transactions on Computational Biology and Bioinformatics ( Volume: 12, Issue: 4, 01 July-Aug. 2015)
Page(s): 778 - 784
Date of Publication: 10 November 2014

ISSN Information:

PubMed ID: 26357316

Funding Agency:


Contact IEEE to Subscribe

References

References is not available for this document.