PastView: a user-friendly interface to explore ancestral scenarios.
BMC Evol Biol
; 19(1): 163, 2019 08 02.
Article
em En
| MEDLINE
| ID: mdl-31375065
ABSTRACT
BACKGROUND:
Ancestral character states computed from the combination of phylogenetic trees with extrinsic traits are used to decipher evolutionary scenarios in various research fields such as phylogeography, epidemiology, and ecology. Despite the existence of powerful methods and software in ancestral character state inference, difficulties may arise when interpreting the outputs of such inferences. The growing complexity of data (trees, annotations), the diversity of optimization criteria for computing trees and ancestral character states, the combinatorial explosion of potential evolutionary scenarios if some ancestral characters states do not stand out clearly from others, requires the design of new methods to explore associations of phylogenetic trees with extrinsic traits, to ease the visualization and interpretation of evolutionary scenarios.RESULT:
We developed PastView, a user-friendly interface that includes numerical and graphical features to help users to import and/or compute ancestral character states from discrete variables and extract ancestral scenarios as sets of successive transitions of character states from the tree root to its leaves. PastView provides summarized views such as transition maps and integrates comparative tools to highlight agreements or discrepancies between methods of ancestral annotations inference.CONCLUSION:
The main contribution of PastView is to assemble known numerical and graphical methods into a multi-maps graphical user interface dedicated to the computing, searching and viewing of evolutionary scenarios based on phylogenetic trees and ancestral character states. PastView is available publicly as a standalone software on www.pastview.org .Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Filogenia
/
Interface Usuário-Computador
/
Software
Limite:
Humans
País/Região como assunto:
Europa
Idioma:
En
Revista:
BMC Evol Biol
Assunto da revista:
BIOLOGIA
Ano de publicação:
2019
Tipo de documento:
Article
País de afiliação:
França