Statistical assignment of DNA sequences using Bayesian phylogenetics

Kasper Munch; Wouter Boomsma; John P. Huelsenbeck; Eske Willerslev; Rasmus Nielsen

doi:10.1080/10635150802422316

Statistical assignment of DNA sequences using Bayesian phylogenetics

Kasper Munch^*, Wouter Boomsma, John P. Huelsenbeck, Eske Willerslev, Rasmus Nielsen

^*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avis › Tidsskriftartikel › Forskning › peer review

116 Citationer (Scopus)

Abstract

We provide a new automated statistical method for DNA barcoding based on a Bayesian phylogenetic analysis. The method is based on automated database sequence retrieval, alignment, and phylogenetic analysis using a custom-built program for Bayesian phylogenetic analysis. We show on real data that the method outperforms Blast searches as a measure of confidence and can help eliminate 80% of all false assignment based on best Blast hit. However, the most important advance of the method is that it provides statistically meaningful measures of confidence. We apply the method to a re-analysis of previously published ancient DNA data and show that, with high statistical confidence, most of the published sequences are in fact of Neanderthal origin. However, there are several cases of chimeric sequences that are comprised of a combination of both Neanderthal and modern human DNA.

Originalsprog	Engelsk
Tidsskrift	Systematic Biology
Vol/bind	57
Nummer	5
Sider (fra-til)	750-757
Antal sider	8
ISSN	1063-5157
DOI	https://doi.org/10.1080/10635150802422316
Status	Udgivet - 1 okt. 2008

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Citationsformater

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AU - Munch, Kasper

AU - Boomsma, Wouter

AU - Huelsenbeck, John P.

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AU - Nielsen, Rasmus

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N2 - We provide a new automated statistical method for DNA barcoding based on a Bayesian phylogenetic analysis. The method is based on automated database sequence retrieval, alignment, and phylogenetic analysis using a custom-built program for Bayesian phylogenetic analysis. We show on real data that the method outperforms Blast searches as a measure of confidence and can help eliminate 80% of all false assignment based on best Blast hit. However, the most important advance of the method is that it provides statistically meaningful measures of confidence. We apply the method to a re-analysis of previously published ancient DNA data and show that, with high statistical confidence, most of the published sequences are in fact of Neanderthal origin. However, there are several cases of chimeric sequences that are comprised of a combination of both Neanderthal and modern human DNA.

AB - We provide a new automated statistical method for DNA barcoding based on a Bayesian phylogenetic analysis. The method is based on automated database sequence retrieval, alignment, and phylogenetic analysis using a custom-built program for Bayesian phylogenetic analysis. We show on real data that the method outperforms Blast searches as a measure of confidence and can help eliminate 80% of all false assignment based on best Blast hit. However, the most important advance of the method is that it provides statistically meaningful measures of confidence. We apply the method to a re-analysis of previously published ancient DNA data and show that, with high statistical confidence, most of the published sequences are in fact of Neanderthal origin. However, there are several cases of chimeric sequences that are comprised of a combination of both Neanderthal and modern human DNA.

KW - Assignment

KW - Barcoding

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KW - Phylogenetics

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M3 - Journal article

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JO - Systematic Biology

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Statistical assignment of DNA sequences using Bayesian phylogenetics

Abstract

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