Reconstruction of microbial haplotypes by integration of statistical and physical linkage in scaffolding

Cao, Chen; He, Jialin; Mak, Lauren; Perera, Deshan; Kwok, Devin; Wang, Jia; Li, Minghao; Mourier, Tobias; Gavriliuc, Stefan; Greenberg, Matthew; Morrissy, A. Sorana; Sycuro, Laura K.; Yang, Guang; Jeffares, Daniel C.; Long, Quan

doi:10.1101/2020.03.29.014704

Cited by 2 publications

(4 citation statements)

References 71 publications

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“…Here we present the major findings from our comparison. We first follow the HIV simulation scenario suggested in [Cao et al, 2020].…”

Section: Methods Comparisonmentioning

confidence: 99%

“…Unfortunately CliqueSNV crashed on our Mac Pro machine with 2,7 GHz 12-Core Intel Xeon E5 Processor with 32 GB RAM due to memory errors. We therefore compared haploSep with another method by [Cao et al, 2020] that took 2631 minutes (≈ 158000s) to run. See SI Section S13-4 for details.…”

Section: Methods Comparisonmentioning

confidence: 99%

“…The methods by [Excoffier and Slatkin, 1995], [Pirinen, 2009], [Gasbarra et al, 2011], [Long et al, 2011], [Kessner et al, 2013] and [Cao and Sun, 2015] use known founder haplotypes, and only estimate the frequency trajectories of these haplotypes over time. To reconstruct microbial strains, methods have been proposed that rely on sequencing read data [Pulido-Tamayo et al, 2015], [Cao et al, 2020], [Knyazev et al, 2018].…”

Section: Introductionmentioning

confidence: 99%

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Multiple Haplotype Reconstruction from Allele Frequency Data

Pelizzola

Behr

et al. 2020

Preprint

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1AbstractWe propose a new method that is able to accurately infer major haplotypes and their frequencies just from multiple samples of allele frequency data. Our approach seems to be the first that is able to estimate more than one haplotype given such data. Even the accuracy of experimentally obtained allele frequencies can be improved by re-estimating them from our reconstructed haplotypes.Reconstructing haplotypes from sequencing data is of interest to several areas of biological and medical research. In evolutionary genetics, for instance, haplotypes help to better understand the genetic architecture of adaptation. Here we consider genomic time series data from three evolve and re-sequence experiments as an application. However, the approach can in principle be used in a wider context, as only data from multiple samples are needed, not necessarily collected over time.

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“…Here we present the major findings from our comparison. We first follow the HIV simulation scenario suggested in [Cao et al, 2020].…”

Section: Methods Comparisonmentioning

confidence: 99%

Section: Methods Comparisonmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Multiple Haplotype Reconstruction from Allele Frequency Data

Pelizzola

Behr

et al. 2020

Preprint

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“…WhatsHap takes a dynamic programming approach that is both fast and more accurate than statistical phasers [ 14 ]. PoolhapX infers haplotypes across naturally pooled samples [ 17 ]. Accuracy for these tools has been determined by consensus to other methods or using simulated data.…”

Section: Introductionmentioning

confidence: 99%

HaplotypeTools: a toolkit for accurately identifying recombination and recombinant genotypes

Farrer

2021

BMC Bioinformatics

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Background Identifying haplotypes is central to sequence analysis in diploid or polyploid genomes. Despite this, there remains a lack of research and tools designed for physical phasing and its downstream analysis. Results HaplotypeTools is a new toolset to phase variant sites using VCF and BAM files and to analyse phased VCFs. Phasing is achieved via the identification of reads overlapping ≥ 2 heterozygous positions and then extended by additional reads, a process that can be parallelized across a computer cluster. HaplotypeTools includes various utility scripts for downstream analysis including crossover detection and phylogenetic placement of haplotypes to other lineages or species. HaplotypeTools was assessed for accuracy against WhatsHap using simulated short and long reads, demonstrating higher accuracy, albeit with reduced haplotype length. HaplotypeTools was also tested on real Illumina data to determine the ancestry of hybrid fungal isolate Batrachochytrium dendrobatidis (Bd) SA-EC3, finding 80% of haplotypes across the genome phylogenetically cluster with parental lineages BdGPL (39%) and BdCAPE (41%), indicating those are the parental lineages. Finally, ~ 99% of phasing was conserved between overlapping phase groups between SA-EC3 and either parental lineage, indicating mitotic gene conversion/parasexuality as the mechanism of recombination for this hybrid isolate. HaplotypeTools is open source and freely available from https://github.com/rhysf/HaplotypeTools under the MIT License. Conclusions HaplotypeTools is a powerful resource for analyzing hybrid or recombinant diploid or polyploid genomes and identifying parental ancestry for sub-genomic regions.

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Reconstruction of microbial haplotypes by integration of statistical and physical linkage in scaffolding

Cited by 2 publications

References 71 publications

Multiple Haplotype Reconstruction from Allele Frequency Data

Multiple Haplotype Reconstruction from Allele Frequency Data

HaplotypeTools: a toolkit for accurately identifying recombination and recombinant genotypes

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