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Haplotype network branch diversity, a new metric combining genetic and topological diversity to compare the complexity of haplotype networks
A common way of illustrating phylogeographic results is through the use of haplotype networks. While these networks help to visualize relationships between individuals, populations, and species, evolutionary studies often only quantitatively analyze genetic diversity among haplotypes and ignore othe...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8244886/ https://www.ncbi.nlm.nih.gov/pubmed/34191803 http://dx.doi.org/10.1371/journal.pone.0251878 |
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author | Garcia, Eric Wright, Daniel Gatins, Remy Roberts, May B. Pinheiro, Hudson T. Salas, Eva Chen, Jei-Ying Winnikoff, Jacob R. Bernardi, Giacomo |
author_facet | Garcia, Eric Wright, Daniel Gatins, Remy Roberts, May B. Pinheiro, Hudson T. Salas, Eva Chen, Jei-Ying Winnikoff, Jacob R. Bernardi, Giacomo |
author_sort | Garcia, Eric |
collection | PubMed |
description | A common way of illustrating phylogeographic results is through the use of haplotype networks. While these networks help to visualize relationships between individuals, populations, and species, evolutionary studies often only quantitatively analyze genetic diversity among haplotypes and ignore other network properties. Here, we present a new metric, haplotype network branch diversity (HBd), as an easy way to quantifiably compare haplotype network complexity. Our metric builds off the logic of combining genetic and topological diversity to estimate complexity previously used by the published metric haplotype network diversity (HNd). However, unlike HNd which uses a combination of network features to produce complexity values that cannot be defined in probabilistic terms, thereby obscuring the values’ implication for a sampled population, HBd uses frequencies of haplotype classes to incorporate topological information of networks, keeping the focus on the population and providing easy-to-interpret probabilistic values for randomly sampled individuals. The goal of this study is to introduce this more intuitive metric and provide an R script that allows researchers to calculate diversity and complexity indices from haplotype networks. A group of datasets, generated manually (model dataset) and based on published data (empirical dataset), were used to illustrate the behavior of HBd and both of its terms, haplotype diversity, and a new index called branch diversity. Results followed a predicted trend in both model and empirical datasets, from low metric values in simple networks to high values in complex networks. In short, the new combined metric joins genetic and topological diversity of haplotype networks, into a single complexity value. Based on our analysis, we recommend the use of HBd, as it makes direct comparisons of network complexity straightforward and provides probabilistic values that can readily discriminate situations that are difficult to resolve with available metrics. |
format | Online Article Text |
id | pubmed-8244886 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-82448862021-07-12 Haplotype network branch diversity, a new metric combining genetic and topological diversity to compare the complexity of haplotype networks Garcia, Eric Wright, Daniel Gatins, Remy Roberts, May B. Pinheiro, Hudson T. Salas, Eva Chen, Jei-Ying Winnikoff, Jacob R. Bernardi, Giacomo PLoS One Research Article A common way of illustrating phylogeographic results is through the use of haplotype networks. While these networks help to visualize relationships between individuals, populations, and species, evolutionary studies often only quantitatively analyze genetic diversity among haplotypes and ignore other network properties. Here, we present a new metric, haplotype network branch diversity (HBd), as an easy way to quantifiably compare haplotype network complexity. Our metric builds off the logic of combining genetic and topological diversity to estimate complexity previously used by the published metric haplotype network diversity (HNd). However, unlike HNd which uses a combination of network features to produce complexity values that cannot be defined in probabilistic terms, thereby obscuring the values’ implication for a sampled population, HBd uses frequencies of haplotype classes to incorporate topological information of networks, keeping the focus on the population and providing easy-to-interpret probabilistic values for randomly sampled individuals. The goal of this study is to introduce this more intuitive metric and provide an R script that allows researchers to calculate diversity and complexity indices from haplotype networks. A group of datasets, generated manually (model dataset) and based on published data (empirical dataset), were used to illustrate the behavior of HBd and both of its terms, haplotype diversity, and a new index called branch diversity. Results followed a predicted trend in both model and empirical datasets, from low metric values in simple networks to high values in complex networks. In short, the new combined metric joins genetic and topological diversity of haplotype networks, into a single complexity value. Based on our analysis, we recommend the use of HBd, as it makes direct comparisons of network complexity straightforward and provides probabilistic values that can readily discriminate situations that are difficult to resolve with available metrics. Public Library of Science 2021-06-30 /pmc/articles/PMC8244886/ /pubmed/34191803 http://dx.doi.org/10.1371/journal.pone.0251878 Text en © 2021 Garcia et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Garcia, Eric Wright, Daniel Gatins, Remy Roberts, May B. Pinheiro, Hudson T. Salas, Eva Chen, Jei-Ying Winnikoff, Jacob R. Bernardi, Giacomo Haplotype network branch diversity, a new metric combining genetic and topological diversity to compare the complexity of haplotype networks |
title | Haplotype network branch diversity, a new metric combining genetic and topological diversity to compare the complexity of haplotype networks |
title_full | Haplotype network branch diversity, a new metric combining genetic and topological diversity to compare the complexity of haplotype networks |
title_fullStr | Haplotype network branch diversity, a new metric combining genetic and topological diversity to compare the complexity of haplotype networks |
title_full_unstemmed | Haplotype network branch diversity, a new metric combining genetic and topological diversity to compare the complexity of haplotype networks |
title_short | Haplotype network branch diversity, a new metric combining genetic and topological diversity to compare the complexity of haplotype networks |
title_sort | haplotype network branch diversity, a new metric combining genetic and topological diversity to compare the complexity of haplotype networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8244886/ https://www.ncbi.nlm.nih.gov/pubmed/34191803 http://dx.doi.org/10.1371/journal.pone.0251878 |
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