Cargando…
A Simple 2D Non-Parametric Resampling Statistical Approach to Assess Confidence in Species Identification in DNA Barcoding—An Alternative to Likelihood and Bayesian Approaches
In the recent worldwide campaign for the global biodiversity inventory via DNA barcoding, a simple and easily used measure of confidence for assigning sequences to species in DNA barcoding has not been established so far, although the likelihood ratio test and the Bayesian approach had been proposed...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3519818/ https://www.ncbi.nlm.nih.gov/pubmed/23239988 http://dx.doi.org/10.1371/journal.pone.0050831 |
_version_ | 1782252744297414656 |
---|---|
author | Jin, Qian He, Li-Jun Zhang, Ai-Bing |
author_facet | Jin, Qian He, Li-Jun Zhang, Ai-Bing |
author_sort | Jin, Qian |
collection | PubMed |
description | In the recent worldwide campaign for the global biodiversity inventory via DNA barcoding, a simple and easily used measure of confidence for assigning sequences to species in DNA barcoding has not been established so far, although the likelihood ratio test and the Bayesian approach had been proposed to address this issue from a statistical point of view. The TDR (Two Dimensional non-parametric Resampling) measure newly proposed in this study offers users a simple and easy approach to evaluate the confidence of species membership in DNA barcoding projects. We assessed the validity and robustness of the TDR approach using datasets simulated under coalescent models, and an empirical dataset, and found that TDR measure is very robust in assessing species membership of DNA barcoding. In contrast to the likelihood ratio test and Bayesian approach, the TDR method stands out due to simplicity in both concepts and calculations, with little in the way of restrictive population genetic assumptions. To implement this approach we have developed a computer program package (TDR1.0beta) freely available from ftp://202.204.209.200/education/video/TDR1.0beta.rar. |
format | Online Article Text |
id | pubmed-3519818 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-35198182012-12-13 A Simple 2D Non-Parametric Resampling Statistical Approach to Assess Confidence in Species Identification in DNA Barcoding—An Alternative to Likelihood and Bayesian Approaches Jin, Qian He, Li-Jun Zhang, Ai-Bing PLoS One Research Article In the recent worldwide campaign for the global biodiversity inventory via DNA barcoding, a simple and easily used measure of confidence for assigning sequences to species in DNA barcoding has not been established so far, although the likelihood ratio test and the Bayesian approach had been proposed to address this issue from a statistical point of view. The TDR (Two Dimensional non-parametric Resampling) measure newly proposed in this study offers users a simple and easy approach to evaluate the confidence of species membership in DNA barcoding projects. We assessed the validity and robustness of the TDR approach using datasets simulated under coalescent models, and an empirical dataset, and found that TDR measure is very robust in assessing species membership of DNA barcoding. In contrast to the likelihood ratio test and Bayesian approach, the TDR method stands out due to simplicity in both concepts and calculations, with little in the way of restrictive population genetic assumptions. To implement this approach we have developed a computer program package (TDR1.0beta) freely available from ftp://202.204.209.200/education/video/TDR1.0beta.rar. Public Library of Science 2012-12-11 /pmc/articles/PMC3519818/ /pubmed/23239988 http://dx.doi.org/10.1371/journal.pone.0050831 Text en © 2012 Jin et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Jin, Qian He, Li-Jun Zhang, Ai-Bing A Simple 2D Non-Parametric Resampling Statistical Approach to Assess Confidence in Species Identification in DNA Barcoding—An Alternative to Likelihood and Bayesian Approaches |
title | A Simple 2D Non-Parametric Resampling Statistical Approach to Assess Confidence in Species Identification in DNA Barcoding—An Alternative to Likelihood and Bayesian Approaches |
title_full | A Simple 2D Non-Parametric Resampling Statistical Approach to Assess Confidence in Species Identification in DNA Barcoding—An Alternative to Likelihood and Bayesian Approaches |
title_fullStr | A Simple 2D Non-Parametric Resampling Statistical Approach to Assess Confidence in Species Identification in DNA Barcoding—An Alternative to Likelihood and Bayesian Approaches |
title_full_unstemmed | A Simple 2D Non-Parametric Resampling Statistical Approach to Assess Confidence in Species Identification in DNA Barcoding—An Alternative to Likelihood and Bayesian Approaches |
title_short | A Simple 2D Non-Parametric Resampling Statistical Approach to Assess Confidence in Species Identification in DNA Barcoding—An Alternative to Likelihood and Bayesian Approaches |
title_sort | simple 2d non-parametric resampling statistical approach to assess confidence in species identification in dna barcoding—an alternative to likelihood and bayesian approaches |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3519818/ https://www.ncbi.nlm.nih.gov/pubmed/23239988 http://dx.doi.org/10.1371/journal.pone.0050831 |
work_keys_str_mv | AT jinqian asimple2dnonparametricresamplingstatisticalapproachtoassessconfidenceinspeciesidentificationindnabarcodinganalternativetolikelihoodandbayesianapproaches AT helijun asimple2dnonparametricresamplingstatisticalapproachtoassessconfidenceinspeciesidentificationindnabarcodinganalternativetolikelihoodandbayesianapproaches AT zhangaibing asimple2dnonparametricresamplingstatisticalapproachtoassessconfidenceinspeciesidentificationindnabarcodinganalternativetolikelihoodandbayesianapproaches AT jinqian simple2dnonparametricresamplingstatisticalapproachtoassessconfidenceinspeciesidentificationindnabarcodinganalternativetolikelihoodandbayesianapproaches AT helijun simple2dnonparametricresamplingstatisticalapproachtoassessconfidenceinspeciesidentificationindnabarcodinganalternativetolikelihoodandbayesianapproaches AT zhangaibing simple2dnonparametricresamplingstatisticalapproachtoassessconfidenceinspeciesidentificationindnabarcodinganalternativetolikelihoodandbayesianapproaches |