| Chapter title |
Species Tree Estimation from Genome-Wide Data with guenomu.
|
|---|---|
| Chapter number | 18 |
| Book title |
Bioinformatics
|
| Published in |
Methods in molecular biology, January 2017
|
| DOI | 10.1007/978-1-4939-6622-6_18 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6620-2, 978-1-4939-6622-6
|
| Authors |
Leonardo de Oliveira Martins, David Posada |
| Editors |
Jonathan M. Keith |
| Abstract |
The history of particular genes and that of the species that carry them can be different for a variety of reasons. In particular, gene trees and species trees can differ due to well-known evolutionary processes such as gene duplication and loss, lateral gene transfer, or incomplete lineage sorting. Species tree reconstruction methods have been developed to take this incongruence into account; these can be divided grossly into supertree and supermatrix approaches. Here we introduce a new Bayesian hierarchical model that we have recently developed and implemented in the program guenomu. The new model considers multiple sources of gene tree/species tree disagreement. Guenomu takes as input posterior distributions of unrooted gene tree topologies for multiple gene families, in order to estimate the posterior distribution of rooted species tree topologies. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 1 | 50% |
| United States | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 5% |
| New Zealand | 1 | 5% |
| Germany | 1 | 5% |
| Unknown | 18 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 29% |
| Researcher | 4 | 19% |
| Other | 2 | 10% |
| Professor | 2 | 10% |
| Professor > Associate Professor | 2 | 10% |
| Other | 2 | 10% |
| Unknown | 3 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 12 | 57% |
| Biochemistry, Genetics and Molecular Biology | 2 | 10% |
| Immunology and Microbiology | 2 | 10% |
| Mathematics | 1 | 5% |
| Medicine and Dentistry | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 2 | 10% |