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Vences M, Patmanidis S, Schmidt JC, Matschiner M, Miralles A, Renner SS. Hapsolutely: a user-friendly tool integrating haplotype phasing, network construction, and haploweb calculation. BIOINFORMATICS ADVANCES 2024; 4:vbae083. [PMID: 38895561 PMCID: PMC11184345 DOI: 10.1093/bioadv/vbae083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 05/15/2024] [Accepted: 06/04/2024] [Indexed: 06/21/2024]
Abstract
Motivation Haplotype networks are a routine approach to visualize relationships among alleles. Such visual analysis of single-locus data is still of importance, especially in species diagnosis and delimitation, where a limited amount of sequence data usually are available and sufficient, along with other datasets in the framework of integrative taxonomy. In diploid organisms, this often requires separating (phasing) sequences with heterozygotic positions, and typically separate programs are required for phasing, reformatting of input files, and haplotype network construction. We therefore developed Hapsolutely, a user-friendly program with an ergonomic graphical user interface that integrates haplotype phasing from single-locus sequences with five approaches for network/genealogy reconstruction. Results Among the novel options implemented, Hapsolutely integrates phasing and graphical reconstruction steps of haplotype networks, supports input of species partition data in the common SPART and SPART-XML formats, and calculates and visualizes haplowebs and fields for recombination, thus allowing graphical comparison of allele distribution and allele sharing among subsets for the purpose of species delimitation. The new tool has been specifically developed with a focus on the workflow in alpha-taxonomy, where exploring fields for recombination across alternative species partitions may help species delimitation. Availability and implementation Hapsolutely is written in Python, and integrates code from Phase, SeqPHASE, and PopART in C++ and Haxe. Compiled stand-alone executables for MS Windows and Mac OS along with a detailed manual can be downloaded from https://www.itaxotools.org; the source code is openly available on GitHub (https://github.com/iTaxoTools/Hapsolutely).
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Affiliation(s)
- Miguel Vences
- Division of Evolutionary Biology, Zoological Institute, Technische Universität Braunschweig, 38106 Braunschweig, Germany
| | - Stefanos Patmanidis
- Department of Computer Science, School of Electrical and Computer Engineering, National Technical University of Athens, 15780 Athens, Greece
| | - Jan-Christopher Schmidt
- Division of Evolutionary Biology, Zoological Institute, Technische Universität Braunschweig, 38106 Braunschweig, Germany
| | | | - Aurélien Miralles
- Division of Evolutionary Biology, Zoological Institute, Technische Universität Braunschweig, 38106 Braunschweig, Germany
- Institut de Systématique, Évolution, Biodiversité (ISYEB), Muséum National d’Histoire Naturelle, CNRS, Sorbonne Université, EPHE, 75005 Paris, France
| | - Susanne S Renner
- Department of Biology, Washington University, Saint Louis, MO 63130, United States
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Garcia E, Wright D, Gatins R, Roberts MB, Pinheiro HT, Salas E, Chen JY, Winnikoff JR, Bernardi G. Haplotype network branch diversity, a new metric combining genetic and topological diversity to compare the complexity of haplotype networks. PLoS One 2021; 16:e0251878. [PMID: 34191803 PMCID: PMC8244886 DOI: 10.1371/journal.pone.0251878] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 05/04/2021] [Indexed: 11/18/2022] Open
Abstract
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.
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Affiliation(s)
- Eric Garcia
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, California, United States of America
- Department of Biological Sciences, Old Dominion University, Norfolk, Virginia, United States of America
| | - Daniel Wright
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, California, United States of America
| | - Remy Gatins
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, California, United States of America
| | - May B. Roberts
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, California, United States of America
| | - Hudson T. Pinheiro
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, California, United States of America
- California Academy of Science, San Francisco, California, United States of America
| | - Eva Salas
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, California, United States of America
- Department of Biology, Cabrillo College, Aptos, California, United States of America
| | - Jei-Ying Chen
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, California, United States of America
| | - Jacob R. Winnikoff
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, California, United States of America
- Monterey Bay Aquarium Research Institute, Moss Landing, California, United States of America
| | - Giacomo Bernardi
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, California, United States of America
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Paradis E. Analysis of haplotype networks: The randomized minimum spanning tree method. Methods Ecol Evol 2018. [DOI: 10.1111/2041-210x.12969] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Emmanuel Paradis
- ISEM, IRD, University of Montpellier, CNRS, EPHE Montpellier France
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