relation: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2071/
title: Building ancestral recombination graphs for whole genomes
creator: Nguyen, Thao
creator: Le, Sy Vinh
creator: Ho, Hai
creator: Le, Si Quang
subject: Information Technology (IT)
subject: ISI-indexed journals
description: Abstract— The Ancestral Recombination Graph (ARG) plays an important role in human population genetics.  Nevertheless, most current ARG inference algorithms are only applicable to small data sets due to their computational  burden. Margarita by Minichiello and Durbin [1] can handle larger data sets; however, it is still not feasible  at genome scale. We hereby propose a heuristic algorithm, called ARG4WG, to construct plausible ARGs from  thousands of whole chromosome samples, in which the so-called longest shared end, i.e. the longest match between  left or right ends of sequences, is used for recombination in the building process. This strategy allows ARG4WG to  significantly reduce the computational cost, by working hundreds to thousands times faster than Margarita.  ARG4WG leads to ARGs with fewer numbers of recombination events on real data sets. Margarita is slightly better  than ARG4WG in reconstructing tree topology on simulated data. The ARGs resulted from our algorithm also performed  reasonably well in an association study with 5560 haplotypes across a whole Chromosome 11 of the Gambia  dataset. These results indicate that ARG4WG is a good candidate for genome-wide association study from  large data sets.
publisher: IEEE
date: 2016
type: Article
type: PeerReviewed
identifier:   Nguyen, Thao and Le, Sy Vinh and Ho, Hai and Le, Si Quang  (2016) Building ancestral recombination graphs for whole genomes.  IEEE/ACM Transactions on Computational Biology and Bioinformatics .    ISSN 1545-5963    (In Press)