Giovanni Marco Dall'Olio1, Ali R Vahdati1, Jaume Bertranpetit1, Andreas Wagner2, Hafid Laayouni3. 1. Department of Experimental and Health Sciences, Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), 08003 Barcelona, Catalonia, Spain, Institute of Evolutionary Biology and Environmental Studies/Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland, SIB, CIG Quartier Sorge, bâtiment Génopode 1015 Lausanne, Switzerland, The Santa Fe Institute, 1399 Hyde Parke Road, 87501 Santa Fe, New Mexico, USA and Departament de Genetica i de Microbiologia, Grup de Biologia Evolutiva (GBE), Universitat Autonoma de Barcelona, 08913 Bellaterra, Barcelona. 2. Department of Experimental and Health Sciences, Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), 08003 Barcelona, Catalonia, Spain, Institute of Evolutionary Biology and Environmental Studies/Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland, SIB, CIG Quartier Sorge, bâtiment Génopode 1015 Lausanne, Switzerland, The Santa Fe Institute, 1399 Hyde Parke Road, 87501 Santa Fe, New Mexico, USA and Departament de Genetica i de Microbiologia, Grup de Biologia Evolutiva (GBE), Universitat Autonoma de Barcelona, 08913 Bellaterra, Barcelona Department of Experimental and Health Sciences, Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), 08003 Barcelona, Catalonia, Spain, Institute of Evolutionary Biology and Environmental Studies/Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland, SIB, CIG Quartier Sorge, bâtiment Génopode 1015 Lausanne, Switzerland, The Santa Fe Institute, 1399 Hyde Parke Road, 87501 Santa Fe, New Mexico, USA and Departament de Genetica i de Microbiologia, Grup de Biologia Evolutiva (GBE), Universitat Autonoma de Barcelona, 08913 Bellaterra, Barcelona Department of Experimental and Health Sciences, Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), 08003 Barcelona, Catalonia, Spain, Institute of Evolutionary Biology and Environmental Studies/Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland, SIB, CIG Quartier Sorge, bâtiment Génopode 1015 Lausanne, Switzerland, The Santa Fe Institute, 1399 Hyde Parke Road, 87501 Santa Fe, New Mexico, USA and Departament de Genetica i de Microbiologia, Grup de Biologia Evolutiva (GBE), Universitat Autonoma de Barcelona, 08913 Bellaterra, Barcelona. 3. Department of Experimental and Health Sciences, Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), 08003 Barcelona, Catalonia, Spain, Institute of Evolutionary Biology and Environmental Studies/Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland, SIB, CIG Quartier Sorge, bâtiment Génopode 1015 Lausanne, Switzerland, The Santa Fe Institute, 1399 Hyde Parke Road, 87501 Santa Fe, New Mexico, USA and Departament de Genetica i de Microbiologia, Grup de Biologia Evolutiva (GBE), Universitat Autonoma de Barcelona, 08913 Bellaterra, Barcelona Department of Experimental and Health Sciences, Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), 08003 Barcelona, Catalonia, Spain, Institute of Evolutionary Biology and Environmental Studies/Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland, SIB, CIG Quartier Sorge, bâtiment Génopode 1015 Lausanne, Switzerland, The Santa Fe Institute, 1399 Hyde Parke Road, 87501 Santa Fe, New Mexico, USA and Departament de Genetica i de Microbiologia, Grup de Biologia Evolutiva (GBE), Universitat Autonoma de Barcelona, 08913 Bellaterra, Barcelona.
Abstract
SUMMARY: A wealth of large-scale genome sequencing projects opens the doors to new approaches to study the relationship between genotype and phenotype. One such opportunity is the possibility to apply genotype networks analysis to population genetics data. Genotype networks are a representation of the set of genotypes associated with a single phenotype, and they allow one to estimate properties such as the robustness of the phenotype to mutations, and the ability of its associated genotypes to evolve new adaptations. So far, though, genotype networks analysis has rarely been applied to population genetics data. To help fill this gap, here we present VCF2Networks, a tool to determine and study genotype network structure from single-nucleotide variant data. AVAILABILITY AND IMPLEMENTATION: VCF2Networks is available at https://bitbucket.org/dalloliogm/vcf2networks. CONTACT: giovanni.dallolio@kcl.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
SUMMARY: A wealth of large-scale genome sequencing projects opens the doors to new approaches to study the relationship between genotype and phenotype. One such opportunity is the possibility to apply genotype networks analysis to population genetics data. Genotype networks are a representation of the set of genotypes associated with a single phenotype, and they allow one to estimate properties such as the robustness of the phenotype to mutations, and the ability of its associated genotypes to evolve new adaptations. So far, though, genotype networks analysis has rarely been applied to population genetics data. To help fill this gap, here we present VCF2Networks, a tool to determine and study genotype network structure from single-nucleotide variant data. AVAILABILITY AND IMPLEMENTATION: VCF2Networks is available at https://bitbucket.org/dalloliogm/vcf2networks. CONTACT: giovanni.dallolio@kcl.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Frank R Wendt; Gita A Pathak; Cassie Overstreet; Daniel S Tylee; Joel Gelernter; Elizabeth G Atkinson; Renato Polimanti Journal: Genomics Date: 2020-12-02 Impact factor: 5.736