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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
biochemistry, genetics and molecular biology
Frequency-based haplotype reconstruction from deep sequencing data of bacterial populations
Nucleic Acids Research, Volume 43, No. 16, Article e105, Year 2015
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Description
Clonal populations accumulate mutations over time, resulting in different haplotypes. Deep sequencing of such a population in principle provides information to reconstruct these haplotypes and the frequency at which the haplotypes occur. However, this reconstruction is technically not trivial, especially not in clonal systems with a relatively low mutation frequency. The low number of segregating sites in those systems adds ambiguity to the haplotype phasing and thus obviates the reconstruction of genome-wide haplotypes based on sequence overlap information. Therefore, we present EVORhA, a haplotype reconstruction method that complements phasing information in the non-empty read overlap with the frequency estimations of inferred local haplotypes. As was shown with simulated data, as soon as read lengths and/or mutation rates become restrictive for state-of-the-art methods, the use of this additional frequency information allows EVORhA to still reliably reconstruct genome-wide haplotypes. On real data, we show the applicability of the method in reconstructing the population composition of evolved bacterial populations and in decomposing mixed bacterial infections from clinical samples. © 2015 The Author(s).
Authors & Co-Authors
Pulido-Tamayo, Sergio
Belgium, Ghent
Universiteit Gent
Belgium, Leuven
Ku Leuven
Sánchez-Rodríguez, Aminael
Belgium, Leuven
Ku Leuven
Ecuador, Loja
Universidad Técnica Particular de Loja
Swings, Toon
Belgium, Leuven
Ku Leuven
Steenackers, Hans P.L.
Belgium, Leuven
Ku Leuven
Michiels, Jan
Belgium, Leuven
Ku Leuven
Fostier, Jan
Belgium, Ghent
Universiteit Gent
Marchal, Kathleen
Belgium, Ghent
Universiteit Gent
Belgium, Leuven
Ku Leuven
Statistics
Citations: 33
Authors: 7
Affiliations: 3
Identifiers
Doi:
10.1093/nar/gkv478
ISSN:
03051048
Research Areas
Cancer
Genetics And Genomics
Study Design
Cross Sectional Study