Yuri T Utsunomiya1, Marco Milanesi2, Adam T H Utsunomiya2, Paolo Ajmone-Marsan3, José F Garcia4. 1. Departamento de Medicina Veterinária Preventiva e Reprodução Animal, UNESP - Univ. Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, 14884-900 Jaboticabal, São Paulo, Brazil International Atomic Energy Agency (IAEA) Collaborating Centre on Animal Genomics and Bioinformatics, 16050-680 Araçatuba, São Paulo, Brazil. 2. International Atomic Energy Agency (IAEA) Collaborating Centre on Animal Genomics and Bioinformatics, 16050-680 Araçatuba, São Paulo, Brazil Departamento de Apoio, Produção e Saúde Animal, UNESP - Univ. Estadual Paulista, Faculdade de Medicina Veterinária de Araçatuba, 16050-680 Araçatuba, São Paulo, Brazil. 3. Istituto di Zootecnica, Università Cattolica del Sacro Cuore, 29122 Piacenza, Italy. 4. Departamento de Medicina Veterinária Preventiva e Reprodução Animal, UNESP - Univ. Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, 14884-900 Jaboticabal, São Paulo, Brazil International Atomic Energy Agency (IAEA) Collaborating Centre on Animal Genomics and Bioinformatics, 16050-680 Araçatuba, São Paulo, Brazil Departamento de Apoio, Produção e Saúde Animal, UNESP - Univ. Estadual Paulista, Faculdade de Medicina Veterinária de Araçatuba, 16050-680 Araçatuba, São Paulo, Brazil.
Abstract
UNLABELLED: The GHap R package was designed to call haplotypes from phased marker data. Given user-defined haplotype blocks (HapBlock), the package identifies the different haplotype alleles (HapAllele) present in the data and scores sample haplotype allele genotypes (HapGenotype) based on HapAllele dose (i.e. 0, 1 or 2 copies). The output is not only useful for analyses that can handle multi-allelic markers, but is also conveniently formatted for existing pipelines intended for bi-allelic markers. AVAILABILITY AND IMPLEMENTATION: https://cran.r-project.org/package=GHap CONTACT: ytutsunomiya@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
UNLABELLED: The GHap R package was designed to call haplotypes from phased marker data. Given user-defined haplotype blocks (HapBlock), the package identifies the different haplotype alleles (HapAllele) present in the data and scores sample haplotype allele genotypes (HapGenotype) based on HapAllele dose (i.e. 0, 1 or 2 copies). The output is not only useful for analyses that can handle multi-allelic markers, but is also conveniently formatted for existing pipelines intended for bi-allelic markers. AVAILABILITY AND IMPLEMENTATION: https://cran.r-project.org/package=GHap CONTACT: ytutsunomiya@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Wilson Nandolo; Yuri T Utsunomiya; Gábor Mészáros; Maria Wurzinger; Negar Khayadzadeh; Rafaela B P Torrecilha; Henry A Mulindwa; Timothy N Gondwe; Patrik Waldmann; Maja Ferenčaković; José F Garcia; Benjamin D Rosen; Derek Bickhart; Curt P van Tassell; Ino Curik; Johann Sölkner Journal: Genet Sel Evol Date: 2018-08-22 Impact factor: 4.297
Authors: Marco Milanesi; Matilde Maria Passamonti; Katia Cappelli; Andrea Minuti; Valentino Palombo; Sandy Sgorlon; Stefano Capomaccio; Mariasilvia D'Andrea; Erminio Trevisi; Bruno Stefanon; John Lewis Williams; Paolo Ajmone-Marsan Journal: Genes (Basel) Date: 2021-04-06 Impact factor: 4.096
Authors: Beatriz B Trigo; Adam T H Utsunomiya; Alvaro A A D Fortunato; Marco Milanesi; Rafaela B P Torrecilha; Harrison Lamb; Loan Nguyen; Elizabeth M Ross; Ben Hayes; Rômulo C M Padula; Thayla S Sussai; Ludmilla B Zavarez; Rafael S Cipriano; Maria M T Caminhas; Flavia L Lopes; Cassiano Pelle; Tosso Leeb; Danika Bannasch; Derek Bickhart; Timothy P L Smith; Tad S Sonstegard; José F Garcia; Yuri T Utsunomiya Journal: Genet Sel Evol Date: 2021-04-28 Impact factor: 4.297
Authors: André Vieira do Nascimento; Ândrea Renata da Silva Romero; Yuri Tani Utsunomiya; Adam Taiti Harth Utsunomiya; Diercles Francisco Cardoso; Haroldo Henrique Rezende Neves; Roberto Carvalheiro; José Fernando Garcia; Alexeia Barufatti Grisolia Journal: PLoS One Date: 2018-08-08 Impact factor: 3.240