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A New Phylogenetic Inference Based on Genetic Attribute Reduction for Morphological Data
To address the instability of phylogenetic trees in morphological datasets caused by missing values, we present a phylogenetic inference method based on a concept decision tree (CDT) in conjunction with attribute reduction. First, a reliable initial phylogenetic seed tree is created using a few spec...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514795/ https://www.ncbi.nlm.nih.gov/pubmed/33267027 http://dx.doi.org/10.3390/e21030313 |
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author | Feng, Jun Liu, Zeyun Feng, Hongwei Sutcliffe, Richard F. E. Liu, Jianni Han, Jian |
author_facet | Feng, Jun Liu, Zeyun Feng, Hongwei Sutcliffe, Richard F. E. Liu, Jianni Han, Jian |
author_sort | Feng, Jun |
collection | PubMed |
description | To address the instability of phylogenetic trees in morphological datasets caused by missing values, we present a phylogenetic inference method based on a concept decision tree (CDT) in conjunction with attribute reduction. First, a reliable initial phylogenetic seed tree is created using a few species with relatively complete morphological information by using biologists’ prior knowledge or by applying existing tools such as MrBayes. Second, using a top-down data processing approach, we construct concept-sample templates by performing attribute reduction at each node in the initial phylogenetic seed tree. In this way, each node is turned into a decision point with multiple concept-sample templates, providing decision-making functions for grafting. Third, we apply a novel matching algorithm to evaluate the degree of similarity between the species’ attributes and their concept-sample templates and to determine the location of the species in the initial phylogenetic seed tree. In this manner, the phylogenetic tree is established step by step. We apply our algorithm to several datasets and compare it with the maximum parsimony, maximum likelihood, and Bayesian inference methods using the two evaluation criteria of accuracy and stability. The experimental results indicate that as the proportion of missing data increases, the accuracy of the CDT method remains at 86.5%, outperforming all other methods and producing a reliable phylogenetic tree. |
format | Online Article Text |
id | pubmed-7514795 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75147952020-11-09 A New Phylogenetic Inference Based on Genetic Attribute Reduction for Morphological Data Feng, Jun Liu, Zeyun Feng, Hongwei Sutcliffe, Richard F. E. Liu, Jianni Han, Jian Entropy (Basel) Article To address the instability of phylogenetic trees in morphological datasets caused by missing values, we present a phylogenetic inference method based on a concept decision tree (CDT) in conjunction with attribute reduction. First, a reliable initial phylogenetic seed tree is created using a few species with relatively complete morphological information by using biologists’ prior knowledge or by applying existing tools such as MrBayes. Second, using a top-down data processing approach, we construct concept-sample templates by performing attribute reduction at each node in the initial phylogenetic seed tree. In this way, each node is turned into a decision point with multiple concept-sample templates, providing decision-making functions for grafting. Third, we apply a novel matching algorithm to evaluate the degree of similarity between the species’ attributes and their concept-sample templates and to determine the location of the species in the initial phylogenetic seed tree. In this manner, the phylogenetic tree is established step by step. We apply our algorithm to several datasets and compare it with the maximum parsimony, maximum likelihood, and Bayesian inference methods using the two evaluation criteria of accuracy and stability. The experimental results indicate that as the proportion of missing data increases, the accuracy of the CDT method remains at 86.5%, outperforming all other methods and producing a reliable phylogenetic tree. MDPI 2019-03-22 /pmc/articles/PMC7514795/ /pubmed/33267027 http://dx.doi.org/10.3390/e21030313 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Feng, Jun Liu, Zeyun Feng, Hongwei Sutcliffe, Richard F. E. Liu, Jianni Han, Jian A New Phylogenetic Inference Based on Genetic Attribute Reduction for Morphological Data |
title | A New Phylogenetic Inference Based on Genetic Attribute Reduction for Morphological Data |
title_full | A New Phylogenetic Inference Based on Genetic Attribute Reduction for Morphological Data |
title_fullStr | A New Phylogenetic Inference Based on Genetic Attribute Reduction for Morphological Data |
title_full_unstemmed | A New Phylogenetic Inference Based on Genetic Attribute Reduction for Morphological Data |
title_short | A New Phylogenetic Inference Based on Genetic Attribute Reduction for Morphological Data |
title_sort | new phylogenetic inference based on genetic attribute reduction for morphological data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514795/ https://www.ncbi.nlm.nih.gov/pubmed/33267027 http://dx.doi.org/10.3390/e21030313 |
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