TY - GEN
T1 - Finding all maximal perfect haplotype blocks in linear time
AU - Alanko, Jarno
AU - Bannai, Hideo
AU - Cazaux, Bastien
AU - Peterlongo, Pierre
AU - Stoye, Jens
N1 - Funding Information:
Funding Hideo Bannai: JSPS KAKENHI Grant Number JP16H02783 Pierre Peterlongo: ANR Hydrogen ANR-14-CE23-0001
Publisher Copyright:
© Jarno N. Alanko, Hideo Bannai, Bastien Cazaux, Pierre Peterlongo, and Jens Stoye; licensed under Creative Commons License CC-BY
PY - 2019/9
Y1 - 2019/9
N2 - Recent large-scale community sequencing efforts allow at an unprecedented level of detail the identification of genomic regions that show signatures of natural selection. Traditional methods for identifying such regions from individuals' haplotype data, however, require excessive computing times and therefore are not applicable to current datasets. In 2019, Cunha et al. (Proceedings of BSB 2019) suggested the maximal perfect haplotype block as a very simple combinatorial pattern, forming the basis of a new method to perform rapid genome-wide selection scans. The algorithm they presented for identifying these blocks, however, had a worst-case running time quadratic in the genome length. It was posed as an open problem whether an optimal, linear-time algorithm exists. In this paper we give two algorithms that achieve this time bound, one conceptually very simple one using suffix trees and a second one using the positional Burrows-Wheeler Transform, that is very efficient also in practice.
AB - Recent large-scale community sequencing efforts allow at an unprecedented level of detail the identification of genomic regions that show signatures of natural selection. Traditional methods for identifying such regions from individuals' haplotype data, however, require excessive computing times and therefore are not applicable to current datasets. In 2019, Cunha et al. (Proceedings of BSB 2019) suggested the maximal perfect haplotype block as a very simple combinatorial pattern, forming the basis of a new method to perform rapid genome-wide selection scans. The algorithm they presented for identifying these blocks, however, had a worst-case running time quadratic in the genome length. It was posed as an open problem whether an optimal, linear-time algorithm exists. In this paper we give two algorithms that achieve this time bound, one conceptually very simple one using suffix trees and a second one using the positional Burrows-Wheeler Transform, that is very efficient also in practice.
UR - http://www.scopus.com/inward/record.url?scp=85072646600&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85072646600&partnerID=8YFLogxK
U2 - 10.4230/LIPIcs.WABI.2019.8
DO - 10.4230/LIPIcs.WABI.2019.8
M3 - Conference contribution
AN - SCOPUS:85072646600
T3 - Leibniz International Proceedings in Informatics, LIPIcs
BT - 19th International Workshop on Algorithms in Bioinformatics, WABI 2019
A2 - Huber, Katharina T.
A2 - Gusfield, Dan
PB - Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
T2 - 19th International Workshop on Algorithms in Bioinformatics, WABI 2019
Y2 - 8 September 2019 through 10 September 2019
ER -