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BHap: a novel approach for bacterial haplotype reconstruction.

ABSTRACT: MOTIVATION:The bacterial haplotype reconstruction is critical for selecting proper treatments for diseases caused by unknown haplotypes. Existing methods and tools do not work well on this task, because they are usually developed for viral instead of bacterial populations. RESULTS:In this study, we developed BHap, a novel algorithm based on fuzzy flow networks, for reconstructing bacterial haplotypes from next generation sequencing data. Tested on simulated and experimental datasets, we showed that BHap was capable of reconstructing haplotypes of bacterial populations with an average F1 score of 0.87, an average precision of 0.87 and an average recall of 0.88. We also demonstrated that BHap had a low susceptibility to sequencing errors, was capable of reconstructing haplotypes with low coverage and could handle a wide range of mutation rates. Compared with existing approaches, BHap outperformed them in terms of higher F1 scores, better precision, better recall and more accurate estimation of the number of haplotypes. AVAILABILITY AND IMPLEMENTATION:The BHap tool is available at http://www.cs.ucf.edu/?xiaoman/BHap/. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.

SUBMITTER: Li X

PROVIDER: S-EPMC6931272 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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BHap: a novel approach for bacterial haplotype reconstruction.

Li Xin X Saadat Samaneh S Hu Haiyan H Li Xiaoman X

Bioinformatics (Oxford, England) 20191101 22

<h4>Motivation</h4>The bacterial haplotype reconstruction is critical for selecting proper treatments for diseases caused by unknown haplotypes. Existing methods and tools do not work well on this task, because they are usually developed for viral instead of bacterial populations.<h4>Results</h4>In this study, we developed BHap, a novel algorithm based on fuzzy flow networks, for reconstructing bacterial haplotypes from next generation sequencing data. Tested on simulated and experimental datase ...[more]

PMID: 31004480

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Project description:BackgroundHaplotype-based approaches have been extensively studied for case-control association mapping in recent years. It has been shown that haplotype methods can provide more consistent results comparing to single-locus based approaches, especially in cases where causal variants are not typed. Improved power has been observed by clustering similar or rare haplotypes into groups to reduce the degrees of freedom of association tests. For family-based association studies, one commonly used strategy is Transmission Disequilibrium Tests (TDT), which examine the imbalanced transmission of alleles/haplotypes to affected and normal children. Many extensions have been developed to deal with general pedigrees and continuous traits.ResultsIn this paper, we propose a new haplotype-based association method for family data that is different from the TDT framework. Our approach (termed F_HapMiner) is based on our previous successful experiences on haplotype inference from pedigree data and haplotype-based association mapping. It first infers diplotype pairs of each individual in each pedigree assuming no recombination within a family. A phenotype score is then defined for each founder haplotype. Finally, F_HapMiner applies a clustering algorithm on those founder haplotypes based on their similarities and identifies haplotype clusters that show significant associations with diseases/traits. We have performed extensive simulations based on realistic assumptions to evaluate the effectiveness of the proposed approach by considering different factors such as allele frequency, linkage disequilibrium (LD) structure, disease model and sample size. Comparisons with single-locus and haplotype-based TDT methods demonstrate that our approach consistently outperforms the TDT-based approaches regardless of disease models, local LD structures or allele/haplotype frequencies.ConclusionWe present a novel haplotype-based association approach using family data. Experiment results demonstrate that it achieves significantly higher power than TDT-based approaches.

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BHap: a novel approach for bacterial haplotype reconstruction.

Publications

BHap: a novel approach for bacterial haplotype reconstruction.

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