Academic Journal
Inference of Ancestral Recombination Graphs through Topological Data Analysis
| Τίτλος: | Inference of Ancestral Recombination Graphs through Topological Data Analysis |
|---|---|
| Συγγραφείς: | Camara, Pablo Gonzales, Levine, Arnold J., Rabadan, Raul |
| Έτος έκδοσης: | 2016 |
| Συλλογή: | Columbia University: Academic Commons |
| Θεματικοί όροι: | Topology--Data processing, Evolution--Mathematical models, Phylogeny, Bioinformatics |
| Περιγραφή: | The recent explosion of genomic data has underscored the need for interpretable and comprehensive analyses that can capture complex phylogenetic relationships within and across species. Recombination, reassortment and horizontal gene transfer constitute examples of pervasive biological phenomena that cannot be captured by tree-like representations. Starting from hundreds of genomes, we are interested in the reconstruction of potential evolutionary histories leading to the observed data. Ancestral recombination graphs represent potential histories that explicitly accommodate recombination and mutation events across orthologous genomes. However, they are computationally costly to reconstruct, usually being infeasible for more than few tens of genomes. Recently, Topological Data Analysis (TDA) methods have been proposed as robust and scalable methods that can capture the genetic scale and frequency of recombination. We build upon previous TDA developments for detecting and quantifying recombination, and present a novel framework that can be applied to hundreds of genomes and can be interpreted in terms of minimal histories of mutation and recombination events, quantifying the scales and identifying the genomic locations of recombinations. We implement this framework in a software package, called TARGet, and apply it to several examples, including small migration between different populations, human recombination, and horizontal evolution in finches inhabiting the Galápagos Islands. |
| Τύπος εγγράφου: | article in journal/newspaper |
| Γλώσσα: | English |
| Relation: | https://doi.org/10.7916/D8416X93 |
| DOI: | 10.7916/D8416X93 |
| Διαθεσιμότητα: | https://doi.org/10.7916/D8416X93 |
| Αριθμός Καταχώρησης: | edsbas.6CBD96CF |
| Βάση Δεδομένων: | BASE |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://doi.org/10.7916/D8416X93# Name: EDS - BASE (ns324271) Category: fullText Text: View record from BASE |
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| Items | – Name: Title Label: Title Group: Ti Data: Inference of Ancestral Recombination Graphs through Topological Data Analysis – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Camara%2C+Pablo+Gonzales%22">Camara, Pablo Gonzales</searchLink><br /><searchLink fieldCode="AR" term="%22Levine%2C+Arnold+J%2E%22">Levine, Arnold J.</searchLink><br /><searchLink fieldCode="AR" term="%22Rabadan%2C+Raul%22">Rabadan, Raul</searchLink> – Name: DatePubCY Label: Publication Year Group: Date Data: 2016 – Name: Subset Label: Collection Group: HoldingsInfo Data: Columbia University: Academic Commons – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Topology--Data+processing%22">Topology--Data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Evolution--Mathematical+models%22">Evolution--Mathematical models</searchLink><br /><searchLink fieldCode="DE" term="%22Phylogeny%22">Phylogeny</searchLink><br /><searchLink fieldCode="DE" term="%22Bioinformatics%22">Bioinformatics</searchLink> – Name: Abstract Label: Description Group: Ab Data: The recent explosion of genomic data has underscored the need for interpretable and comprehensive analyses that can capture complex phylogenetic relationships within and across species. Recombination, reassortment and horizontal gene transfer constitute examples of pervasive biological phenomena that cannot be captured by tree-like representations. Starting from hundreds of genomes, we are interested in the reconstruction of potential evolutionary histories leading to the observed data. Ancestral recombination graphs represent potential histories that explicitly accommodate recombination and mutation events across orthologous genomes. However, they are computationally costly to reconstruct, usually being infeasible for more than few tens of genomes. Recently, Topological Data Analysis (TDA) methods have been proposed as robust and scalable methods that can capture the genetic scale and frequency of recombination. We build upon previous TDA developments for detecting and quantifying recombination, and present a novel framework that can be applied to hundreds of genomes and can be interpreted in terms of minimal histories of mutation and recombination events, quantifying the scales and identifying the genomic locations of recombinations. We implement this framework in a software package, called TARGet, and apply it to several examples, including small migration between different populations, human recombination, and horizontal evolution in finches inhabiting the Galápagos Islands. – Name: TypeDocument Label: Document Type Group: TypDoc Data: article in journal/newspaper – Name: Language Label: Language Group: Lang Data: English – Name: NoteTitleSource Label: Relation Group: SrcInfo Data: https://doi.org/10.7916/D8416X93 – Name: DOI Label: DOI Group: ID Data: 10.7916/D8416X93 – Name: URL Label: Availability Group: URL Data: https://doi.org/10.7916/D8416X93 – Name: AN Label: Accession Number Group: ID Data: edsbas.6CBD96CF |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.7916/D8416X93 Languages: – Text: English Subjects: – SubjectFull: Topology--Data processing Type: general – SubjectFull: Evolution--Mathematical models Type: general – SubjectFull: Phylogeny Type: general – SubjectFull: Bioinformatics Type: general Titles: – TitleFull: Inference of Ancestral Recombination Graphs through Topological Data Analysis Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Camara, Pablo Gonzales – PersonEntity: Name: NameFull: Levine, Arnold J. – PersonEntity: Name: NameFull: Rabadan, Raul IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2016 Identifiers: – Type: issn-locals Value: edsbas – Type: issn-locals Value: edsbas.oa |
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