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Building ancestral recombination graphs for whole genomes

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)

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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.

Item Type: Article
Subjects: Information Technology (IT)
ISI-indexed journals
Divisions: Faculty of Information Technology (FIT)
Depositing User: Asso.Prof. Vinh Le
Date Deposited: 05 Dec 2016 03:13
Last Modified: 05 Dec 2016 03:13

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