BHap: a novel approach for bacterial haplotype reconstruction.
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ABSTRACT:
SUBMITTER: Li X
PROVIDER: S-EPMC6931272 | biostudies-literature | 2019 Nov
REPOSITORIES: biostudies-literature
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Project 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.
| S-EPMC4652744 | biostudies-literature
Project description:Many investigators are now using haplotype-tagging single-nucleotide polymorphism (htSNPs) as a way of screening regions of the genome for association with disease. A common approach is to genotype htSNPs in a study population and to use this information to draw inferences about each individual's haplotypic makeup, including SNPs that were not directly genotyped. To test the validity of this approach, we simulated the exercise of typing htSNPs in a large sample of individuals and compared the true and inferred haplotypes. The accuracy of haplotype inference varied, depending on the method of selecting htSNPs, the linkage-disequilibrium structure of the region, and the amount of missing data. At the stage of selection of htSNPs, haplotype-block-based methods required a larger number of htSNPs than did unstructured methods but gave lower levels of error in haplotype inference, particularly when there was a significant amount of missing data. We present a Web-based utility that allows investigators to compare the likely error rates of different sets of htSNPs and to arrive at an economical set of htSNPs that provides acceptable levels of accuracy in haplotype inference.
| S-EPMC1196396 | biostudies-literature
Project description:Rapid advances in high-throughput DNA sequencing technologies are accelerating the pace of research into personalized medicine. While methods for variant discovery and genotyping from whole genome sequencing (WGS) datasets have been well established, linking variants together into a single haplotype remains a challenge. An understanding of complete haplotypes of an individual will help clarify the consequences of inheriting multiple alleles in combination, identify novel disease associations, and augment studies of gene regulation. Although numerous methods have been developed to reconstruct haplotypes from WGS data, chromosome-span haplotypes at high resolution have been difficult to obtain. Here we present a novel method to accurately reconstruct chromosome-span haplotypes from proximity-ligation and DNA shotgun sequencing. We demonstrate the utility of this approach in producing high-resolution chromosome-span haplotype phasing in mouse and human. While proximity-ligation based methods were originally designed to investigate spatial organization of the genome, our results lend support for their use as a general tool for haplotyping in the future. Hi-C experiments in two replicates of Human GM12878 Lymphoblastoid cells and two replicates of F123 mouse ES cells (4 total samples)
2013-11-03 | E-GEOD-48592 | biostudies-arrayexpress
Project description:BackgroundSingle individual haplotype problem refers to reconstructing haplotypes of an individual based on several input fragments sequenced from a specified chromosome. Solving this problem is an important task in computational biology and has many applications in the pharmaceutical industry, clinical decision-making, and genetic diseases. It is known that solving the problem is NP-hard. Although several methods have been proposed to solve the problem, it is found that most of them have low performances in dealing with noisy input fragments. Therefore, proposing a method which is accurate and scalable, is a challenging task.ResultsIn this paper, we introduced a method, named NCMHap, which utilizes the Neutrosophic c-means (NCM) clustering algorithm. The NCM algorithm can effectively detect the noise and outliers in the input data. In addition, it can reduce their effects in the clustering process. The proposed method has been evaluated by several benchmark datasets. Comparing with existing methods indicates when NCM is tuned by suitable parameters, the results are encouraging. In particular, when the amount of noise increases, it outperforms the comparing methods.ConclusionThe proposed method is validated using simulated and real datasets. The achieved results recommend the application of NCMHap on the datasets which involve the fragments with a huge amount of gaps and noise.
| S-EPMC7579908 | biostudies-literature
Project description:Rapid advances in high-throughput DNA sequencing technologies are accelerating the pace of research into personalized medicine. While methods for variant discovery and genotyping from whole genome sequencing (WGS) datasets have been well established, linking variants together into a single haplotype remains a challenge. An understanding of complete haplotypes of an individual will help clarify the consequences of inheriting multiple alleles in combination, identify novel disease associations, and augment studies of gene regulation. Although numerous methods have been developed to reconstruct haplotypes from WGS data, chromosome-span haplotypes at high resolution have been difficult to obtain. Here we present a novel method to accurately reconstruct chromosome-span haplotypes from proximity-ligation and DNA shotgun sequencing. We demonstrate the utility of this approach in producing high-resolution chromosome-span haplotype phasing in mouse and human. While proximity-ligation based methods were originally designed to investigate spatial organization of the genome, our results lend support for their use as a general tool for haplotyping in the future.
2013-11-03 | GSE48592 | GEO
Project description:Next generation sequencing (NGS) has been increasingly applied to characterize viral evolution during HIV and SIV infections. In particular, NGS datasets sampled during the initial months of infection are characterized by relatively low levels of diversity as well as convergent evolution at multiple loci dispersed across the viral genome. Consequently, fully characterizing viral evolution from NGS datasets requires haplotype reconstruction across large regions of the viral genome. Existing haplotype reconstruction algorithms have not been developed with the particular characteristics of early HIV/SIV infection in mind, raising the possibility that better performance could be achieved through a specifically designed algorithm.Here, we introduce a haplotype reconstruction algorithm, RegressHaplo, specifically designed for low diversity and convergent evolution regimes. The algorithm uses a penalized regression that balances a data fitting term with a penalty term that encourages solutions with few haplotypes. The regression covariates are a large set of potential haplotypes and fitting the regression is made computationally feasible by the low diversity setting. Using simulated and in vivo datasets, we compare RegressHaplo to PredictHaplo and QuRe, two existing haplotype reconstruction algorithms. RegressHaplo performs better than these algorithms on simulated datasets with relatively low diversity levels. We suggest RegressHaplo as a novel tool for the investigation of early infection HIV/SIV datasets and, more generally, low diversity viral NGS datasets.sr286@georgetown.edu.https://github.com/SLeviyang/RegressHaplo.
| S-EPMC5870767 | biostudies-literature
Project description:BackgroundThe replacement of tracheal defects has been a challenge for investigators worldwide. We aimed to develop autologous nail grafts for the reconstruction of anterior tracheal defects.MethodsToenail grafts were implanted to improve the structural integrity of the trachea in patients with tracheal diseases. We clinically applied these grafts for the partial replacement of the cervical tracheal cartilage. Data on graft construction details, clinical outcomes, bronchoscopy, and 3-dimensional computed tomography examinations were collected.ResultsThe nail grafts were implanted in 4 patients. The trachea was successfully reconstructed in all cases. Bronchoscopy was performed 3 times to document healing: immediately, 1 month, and 3 months after surgery. All grafts were well vascularized and incorporated into the tracheal wall and were covered with the respiratory mucosa. Three of the patients survived during the study period, but 1 patient died of progressive lung cancer.ConclusionsToenail grafts potentially may be used as an alternative strategy for the closure of small defects during tracheal reconstruction.
| S-EPMC8691915 | biostudies-literature
Project description:High-quality chromosome-scale haplotype sequences of diploid genomes, polyploid genomes, and metagenomes provide important insights into genetic variation associated with disease and biodiversity. However, whole-genome short read sequencing does not yield haplotype information spanning whole chromosomes directly. Computational assembly of shorter haplotype fragments is required for haplotype reconstruction, which can be challenging owing to limited fragment lengths and high haplotype and repeat variability across genomes. Recent advancements in long-read and chromosome-scale sequencing technologies, alongside computational innovations, are improving the reconstruction of haplotypes at the level of whole chromosomes. Here, we review recent and discuss methodological progress and perspectives in these areas.
| S-EPMC8040228 | biostudies-literature
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.
| S-EPMC3009518 | biostudies-literature
Project description:Breast cancer is the most prevalent cancer and second leading cause of cancer-related deaths in both the US and UK female population, a prominent cause of morbidity and cost to both health services. All surgically fit patients are offered breast reconstruction following the initial surgery, and this is traditionally an open approach: either implant-based or an autologous tissue flap. Both lead to scarring that is difficult to conceal. This paper aims to evaluate the novel minimally invasive technique of robotic-assisted surgery. Methods:A systematic review was conducted using Medline (OvidSP) and Embase (OvidSP) to evaluate the current application of robotic-assisted surgery in breast surgery and reconstruction. Results:Twenty-one articles were identified and discussed, composing of level 4 and 5 evidence comparing different surgeons' experiences, techniques, and outcomes. To date, the robotic system has been utilized to harvest the latissimus dorsi muscle for use as a tissue flap (total harvest time of 92 minutes), to perform nipple-sparing mastectomy with immediate breast reconstruction (total operation time 85 minutes) and lately to harvest a deep inferior epigastric perforator flap via an intraabdominal approach. Conclusions:Robotic-assisted surgery can successfully and reproducibly perform a nipple-sparing mastectomy with breast reconstruction. It can minimize the size of scarring and is superior to the laparoscopic technique, with improved 3-dimensional visualization, dexterity, and range of motion able to guide around the curvature of the breast. The main limiting factors are the lack of the US Food and Drug Administration approval, cost of the robot, and specialized skills required.
| S-EPMC7015621 | biostudies-literature