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Performance comparison between bootstrap and multiscale bootstrap for assessing phylogenetic tree for RNA polymerase

Phylogenetic inference refers to the reconstruction of evolutionary relationships among various species that is usually presented in the form of a tree. This study constructs the phylogenetic tree by using a novel distance-based method known as Modified one step M-estimator (MOM) method. The branche...

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Main Authors: Safinah Sharuddin,, Nora Muda,
Format: Article
Language:English
Published: Universiti Kebangsaan Malaysia 2015
Online Access:http://journalarticle.ukm.my/9374/1/15_Safinah_.pdf
http://journalarticle.ukm.my/9374/
http://www.ukm.my/jsm/malay_journals/jilid44bil11_2015/KandunganJilid44Bil11_2015.html
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spelling my-ukm.journal.93742016-12-14T06:49:44Z http://journalarticle.ukm.my/9374/ Performance comparison between bootstrap and multiscale bootstrap for assessing phylogenetic tree for RNA polymerase Safinah Sharuddin, Nora Muda, Phylogenetic inference refers to the reconstruction of evolutionary relationships among various species that is usually presented in the form of a tree. This study constructs the phylogenetic tree by using a novel distance-based method known as Modified one step M-estimator (MOM) method. The branches of the phylogenetic tree constructed were then evaluated to see their reliability. The performance of the reliability was then compared between the p-value of multiscale bootstrap (AU value) and bootstrap p-value (BP value). The aim of this study was to compare the performance between the AU value and BP value for assessing phylogenetic tree of RNA polymerase. The results have shown that multiscale bootstrap analysis can detect high sampling errors but not in bootstrap analysis. To overcome this problem, the multiscale bootstrap analysis has reduced the sampling error by increasing the number of replications. The clusters were indicated as significant if AU values or BP values were 95% or higher. From the analysis, the results showed that the BP and AU values differ at 11th and 15th branch of the phylogenetic tree. The BP values at both branches were 72 and 85%, respectively, thereby making the cluster not significant but by looking at the AU values, the two branches were more than 95% and the clusters were significant. This was due to the biasness in calculation of the probability of bootstrap analysis, therefore, the multiscale bootstrap analysis has improved the calculation of the probability value compared to the bootstrap analysis. Universiti Kebangsaan Malaysia 2015-11 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/9374/1/15_Safinah_.pdf Safinah Sharuddin, and Nora Muda, (2015) Performance comparison between bootstrap and multiscale bootstrap for assessing phylogenetic tree for RNA polymerase. Sains Malaysiana, 44 (11). pp. 1643-1651. ISSN 0126-6039 http://www.ukm.my/jsm/malay_journals/jilid44bil11_2015/KandunganJilid44Bil11_2015.html
institution Universiti Kebangsaan Malaysia
building Perpustakaan Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
language English
description Phylogenetic inference refers to the reconstruction of evolutionary relationships among various species that is usually presented in the form of a tree. This study constructs the phylogenetic tree by using a novel distance-based method known as Modified one step M-estimator (MOM) method. The branches of the phylogenetic tree constructed were then evaluated to see their reliability. The performance of the reliability was then compared between the p-value of multiscale bootstrap (AU value) and bootstrap p-value (BP value). The aim of this study was to compare the performance between the AU value and BP value for assessing phylogenetic tree of RNA polymerase. The results have shown that multiscale bootstrap analysis can detect high sampling errors but not in bootstrap analysis. To overcome this problem, the multiscale bootstrap analysis has reduced the sampling error by increasing the number of replications. The clusters were indicated as significant if AU values or BP values were 95% or higher. From the analysis, the results showed that the BP and AU values differ at 11th and 15th branch of the phylogenetic tree. The BP values at both branches were 72 and 85%, respectively, thereby making the cluster not significant but by looking at the AU values, the two branches were more than 95% and the clusters were significant. This was due to the biasness in calculation of the probability of bootstrap analysis, therefore, the multiscale bootstrap analysis has improved the calculation of the probability value compared to the bootstrap analysis.
format Article
author Safinah Sharuddin,
Nora Muda,
spellingShingle Safinah Sharuddin,
Nora Muda,
Performance comparison between bootstrap and multiscale bootstrap for assessing phylogenetic tree for RNA polymerase
author_facet Safinah Sharuddin,
Nora Muda,
author_sort Safinah Sharuddin,
title Performance comparison between bootstrap and multiscale bootstrap for assessing phylogenetic tree for RNA polymerase
title_short Performance comparison between bootstrap and multiscale bootstrap for assessing phylogenetic tree for RNA polymerase
title_full Performance comparison between bootstrap and multiscale bootstrap for assessing phylogenetic tree for RNA polymerase
title_fullStr Performance comparison between bootstrap and multiscale bootstrap for assessing phylogenetic tree for RNA polymerase
title_full_unstemmed Performance comparison between bootstrap and multiscale bootstrap for assessing phylogenetic tree for RNA polymerase
title_sort performance comparison between bootstrap and multiscale bootstrap for assessing phylogenetic tree for rna polymerase
publisher Universiti Kebangsaan Malaysia
publishDate 2015
url http://journalarticle.ukm.my/9374/1/15_Safinah_.pdf
http://journalarticle.ukm.my/9374/
http://www.ukm.my/jsm/malay_journals/jilid44bil11_2015/KandunganJilid44Bil11_2015.html
_version_ 1643737770972151808
score 13.211869

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