Network-based hierarchical population structure analysis for large genomic data sets Article Swipe
Gili Greenbaum
,
Amir Rubin
,
Alan R. Templeton
,
Noah A. Rosenberg
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1101/gr.250092.119
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1101/gr.250092.119
Analysis of population structure in natural populations using genetic data is a common practice in ecological and evolutionary studies. With large genomic data sets 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 data sets, 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 show the approach by analyzing population structure in the model plant species Arabidopsis thaliana and in human populations. These examples illustrate how network-based approaches for population structure analysis are well-suited to extracting valuable ecological and evolutionary information in the era of large genomic data sets.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1101/gr.250092.119
- http://genome.cshlp.org/content/29/12/2020.full.pdf
- OA Status
- hybrid
- Cited By
- 44
- References
- 86
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2983922107
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2983922107Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/gr.250092.119Digital Object Identifier
- Title
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Network-based hierarchical population structure analysis for large genomic data setsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2019Year of publication
- Publication date
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2019-11-06Full 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
-
https://doi.org/10.1101/gr.250092.119Publisher landing page
- PDF URL
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https://genome.cshlp.org/content/29/12/2020.full.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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hybridOpen access status per OpenAlex
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https://genome.cshlp.org/content/29/12/2020.full.pdfDirect OA link when available
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Biology, Computational biology, Population, Population structure, Genetics, Evolutionary biology, Sociology, DemographyTop concepts (fields/topics) attached by OpenAlex
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44Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 34, 2023: 3, 2022: 4, 2021: 1Per-year citation counts (last 5 years)
- References (count)
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86Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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