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On calculating the probability of a set of orthologous sequences
Probabilistic DNA sequence models have been intensively applied to genome research. Within the evolutionary biology framework, this article investigates the feasibility for rigorously estimating the probability of a set of orthologous DNA sequences which evolve from a common progenitor. We propose M...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3169941/ https://www.ncbi.nlm.nih.gov/pubmed/21918614 |
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author | Liu, Junfeng Chen, Liang Zhao, Hongyu Moore, Dirk F Lin, Yong Shih, Weichung Joe |
author_facet | Liu, Junfeng Chen, Liang Zhao, Hongyu Moore, Dirk F Lin, Yong Shih, Weichung Joe |
author_sort | Liu, Junfeng |
collection | PubMed |
description | Probabilistic DNA sequence models have been intensively applied to genome research. Within the evolutionary biology framework, this article investigates the feasibility for rigorously estimating the probability of a set of orthologous DNA sequences which evolve from a common progenitor. We propose Monte Carlo integration algorithms to sample the unknown ancestral and/or root sequences a posteriori conditional on a reference sequence and apply pairwise Needleman–Wunsch alignment between the sampled and nonreference species sequences to estimate the probability. We test our algorithms on both simulated and real sequences and compare calculated probabilities from Monte Carlo integration to those induced by single multiple alignment. |
format | Online Article Text |
id | pubmed-3169941 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-31699412011-09-14 On calculating the probability of a set of orthologous sequences Liu, Junfeng Chen, Liang Zhao, Hongyu Moore, Dirk F Lin, Yong Shih, Weichung Joe Adv Appl Bioinforma Chem Original Research Probabilistic DNA sequence models have been intensively applied to genome research. Within the evolutionary biology framework, this article investigates the feasibility for rigorously estimating the probability of a set of orthologous DNA sequences which evolve from a common progenitor. We propose Monte Carlo integration algorithms to sample the unknown ancestral and/or root sequences a posteriori conditional on a reference sequence and apply pairwise Needleman–Wunsch alignment between the sampled and nonreference species sequences to estimate the probability. We test our algorithms on both simulated and real sequences and compare calculated probabilities from Monte Carlo integration to those induced by single multiple alignment. Dove Medical Press 2009-02-26 /pmc/articles/PMC3169941/ /pubmed/21918614 Text en © 2009 Liu et al, publisher and licensee Dove Medical Press Ltd. This is an Open Access article which permits unrestricted noncommercial use, provided the original work is properly cited. |
spellingShingle | Original Research Liu, Junfeng Chen, Liang Zhao, Hongyu Moore, Dirk F Lin, Yong Shih, Weichung Joe On calculating the probability of a set of orthologous sequences |
title | On calculating the probability of a set of orthologous sequences |
title_full | On calculating the probability of a set of orthologous sequences |
title_fullStr | On calculating the probability of a set of orthologous sequences |
title_full_unstemmed | On calculating the probability of a set of orthologous sequences |
title_short | On calculating the probability of a set of orthologous sequences |
title_sort | on calculating the probability of a set of orthologous sequences |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3169941/ https://www.ncbi.nlm.nih.gov/pubmed/21918614 |
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