Network-based hierarchical population structure analysis for large genomic datasets Article Swipe
YOU?
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· 2019
· Open Access
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· DOI: https://doi.org/10.1101/518696
Analysis of population structure in natural populations using genetic data is a common practice in ecological and evolutionary studies. With large genomic datasets of populations now appearing more frequently across the taxonomic spectrum, it is becoming increasingly possible to reveal many hierarchical levels of structure, including fine-scale genetic clusters. To analyze these datasets, methods need to be appropriately suited to the challenges of extracting multilevel structure from whole-genome data. Here, we present a network-based approach for constructing population structure representations from genetic data. The use of community detection algorithms from network theory generates a natural hierarchical perspective on the representation that the method produces. The method is computationally efficient, and it requires relatively few assumptions regarding the biological processes that underlie the data. We demonstrate the approach by analyzing population structure in the model plant species Arabidopsis thaliana and in human populations. These examples illustrates how network-based approaches for population structure analysis are well-suited to extracting valuable ecological and evolutionary information in the era of large genomic datasets.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/518696
- https://www.biorxiv.org/content/biorxiv/early/2019/09/23/518696.full.pdf
- OA Status
- green
- Cited By
- 1
- References
- 85
- Related Works
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- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W2911002376Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/518696Digital Object Identifier
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Network-based hierarchical population structure analysis for large genomic datasetsWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2019Year of publication
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2019-01-11Full publication date if available
- Authors
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Gili Greenbaum, Amir Rubin, Alan R. Templeton, Noah A. RosenbergList of authors in order
- Landing page
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https://doi.org/10.1101/518696Publisher landing page
- PDF URL
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https://www.biorxiv.org/content/biorxiv/early/2019/09/23/518696.full.pdfDirect link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://www.biorxiv.org/content/biorxiv/early/2019/09/23/518696.full.pdfDirect OA link when available
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Population, Computer science, Representation (politics), Data mining, Perspective (graphical), Data science, Artificial intelligence, Political science, Sociology, Demography, Politics, LawTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| corresponding_institution_ids | https://openalex.org/I97018004 |
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