Title: The minimum weight clique partition problem and its application to structural variant calling

Authors: Matthew Hayes; Derrick Mullins

Addresses: Department of Physics and Computer Science, Xavier University of Louisiana, New Orleans, Louisiana, 70125, USA ' Department of Physics and Computer Science, Xavier University of Louisiana, New Orleans, Louisiana, 70125, USA

Abstract: The calling of genomic structural variants (SV) in high-throughput sequencing data necessitates prior discovery of abnormally aligned discordant read pair clusters that indicate candidate SVs. Some methods for SV discovery collect these candidate variants by heuristically searching for maximal cliques in an undirected graph, with nodes representing discordant read pairs and edges between vertices indicating that the read pairs overlap. This approach works well for identifying clusters that overlap with noisy mapping artefacts, but could miss distinct variant clusters that are created due to complex structural variants or overlapping breakpoints of distinct SVs. In this paper, we consider the minimum weight clique partition problem and its application to the problem of discordant read pair clustering. Our results demonstrate that methods which approximate or heuristically solve this problem can enhance the predictive abilities of structural variant calling algorithms.

Keywords: clique; structural variant; minimum weight clique; minimum weight clique partition; memoisation; complex structural variant; genomic rearrangement; discordant read; discordant read pair clustering; clustering.

DOI: 10.1504/IJCBDD.2020.113829

International Journal of Computational Biology and Drug Design, 2020 Vol.13 No.5/6, pp.475 - 487

Received: 18 Sep 2019
Accepted: 04 Jun 2020
Published online: 31 Mar 2021 *

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