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/ http://journalarticle.ukm.my/9374/ http://journalarticle.ukm.my/9374/1/15_Safinah_.pdf

id	ukm-9374
recordtype	eprints
spelling	ukm-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
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Kebangasaan Malaysia
building	UKM Institutional Repository
collection	Online Access
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/ http://journalarticle.ukm.my/9374/ http://journalarticle.ukm.my/9374/1/15_Safinah_.pdf
first_indexed	2023-09-18T19:54:41Z
last_indexed	2023-09-18T19:54:41Z
_version_	1777406450216206336

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

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