Improved Algorithmic Complexity for the 3SEQ Recombination Detection Algorithm

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 computa...

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Vydáno v:Molecular biology and evolution Ročník 35; číslo 1; s. 247 - 251
Hlavní autoři: Lam, Ha Minh, Ratmann, Oliver, Boni, Maciej F
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States Oxford University Press 01.01.2018
Témata:
Algorithms
Biology
Complexity
Computation
Datasets
Gene Rearrangement - genetics
Genomes
Infectious diseases
Methods
Mosaicism
Nucleotide sequence
Phylogeny
Probability
Recombinants
Recombination
Recombination, Genetic - genetics
Sequence Alignment - methods
Sequence Analysis, DNA - methods
Sequence Analysis, DNA - statistics & numerical data
Software
Statistical analysis
Statistical methods
Variables
nonparametric
recombination
mosaic structure
ISSN:0737-4038, 1537-1719, 1537-1719
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Shrnutí: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.
Bibliografie:ObjectType-Article-1
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Associate editor: Sergei Kosakovsky Pond
ISSN:0737-4038
1537-1719
1537-1719
DOI:10.1093/molbev/msx263