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Two Methods for Mapping and Visualizing Associated Data on Phylogeny Using Ggtree.
Yu, Guangchuang; Lam, Tommy Tsan-Yuk; Zhu, Huachen; Guan, Yi.
Afiliação
  • Yu G; Institute of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong, China.
  • Lam TT; State Key Laboratory of Emerging Infectious Diseases and Centre of Influenza Research, School of Public Health, The University of Hong Kong, Hong Kong SAR, China.
  • Zhu H; State Key Laboratory of Emerging Infectious Diseases and Centre of Influenza Research, School of Public Health, The University of Hong Kong, Hong Kong SAR, China.
  • Guan Y; Joint Institute of Virology (Shantou University-The University of Hong Kong), Shantou University, Shantou, Guangdong, China.
Mol Biol Evol ; 35(12): 3041-3043, 2018 12 01.
Article em En | MEDLINE | ID: mdl-30351396
ABSTRACT
Ggtree is a comprehensive R package for visualizing and annotating phylogenetic trees with associated data. It can also map and visualize associated external data on phylogenies with two general methods. Method 1 allows external data to be mapped on the tree structure and used as visual characteristic in tree and data visualization. Method 2 plots the data with the tree side by side using different geometric functions after reordering the data based on the tree structure. These two methods integrate data with phylogeny for further exploration and comparison in the evolutionary biology context. Ggtree is available from http//www.bioconductor.org/packages/ggtree.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Filogenia / Software / Técnicas Genéticas Tipo de estudo: Evaluation_studies / Risk_factors_studies Idioma: En Revista: Mol Biol Evol Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2018 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Filogenia / Software / Técnicas Genéticas Tipo de estudo: Evaluation_studies / Risk_factors_studies Idioma: En Revista: Mol Biol Evol Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2018 Tipo de documento: Article País de afiliação: China