Improved Algorithmic Complexity for the 3SEQ Recombination Detection Algorithm

Author:

Lam Ha Minh12,Ratmann Oliver3,Boni Maciej F124

Affiliation:

1. Wellcome Trust Major Overseas Programme, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam

2. Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom

3. MRC Centre for Outbreak Analyses and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom

4. Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, PA

Abstract

Abstract Identifying recombinant sequences in an era of large genomic databases is challenging as it requires an efficient algorithm to identify candidate recombinants and parents, as well as appropriate statistical methods to correct for the large number of comparisons performed. In 2007, a computation was introduced for an exact nonparametric mosaicism statistic that gave high-precision P values for putative recombinants. This exact computation meant that multiple-comparisons corrected P values also had high precision, which is crucial when performing millions or billions of tests in large databases. Here, we introduce an improvement to the algorithmic complexity of this computation from O(mn3) to O(mn2), where m and n are the numbers of recombination-informative sites in the candidate recombinant. This new computation allows for recombination analysis to be performed in alignments with thousands of polymorphic sites. Benchmark runs are presented on viral genome sequence alignments, new features are introduced, and applications outside recombination analysis are discussed.

Funder

Wellcome

Wellcome Trust

Publisher

Oxford University Press (OUP)

Subject

Genetics,Molecular Biology,Ecology, Evolution, Behavior and Systematics

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