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EMIRGE: reconstruction of full-length ribosomal genes from microbial community short read sequencing data

Recovery of ribosomal small subunit genes by assembly of short read community DNA sequence data generally fails, making taxonomic characterization difficult. Here, we solve this problem with a novel iterative method, based on the expectation maximization algorithm, that reconstructs full-length smal...

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Detalles Bibliográficos
Autores principales: Miller, Christopher S, Baker, Brett J, Thomas, Brian C, Singer, Steven W, Banfield, Jillian F
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3219967/
https://www.ncbi.nlm.nih.gov/pubmed/21595876
http://dx.doi.org/10.1186/gb-2011-12-5-r44
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author Miller, Christopher S
Baker, Brett J
Thomas, Brian C
Singer, Steven W
Banfield, Jillian F
author_facet Miller, Christopher S
Baker, Brett J
Thomas, Brian C
Singer, Steven W
Banfield, Jillian F
author_sort Miller, Christopher S
collection PubMed
description Recovery of ribosomal small subunit genes by assembly of short read community DNA sequence data generally fails, making taxonomic characterization difficult. Here, we solve this problem with a novel iterative method, based on the expectation maximization algorithm, that reconstructs full-length small subunit gene sequences and provides estimates of relative taxon abundances. We apply the method to natural and simulated microbial communities, and correctly recover community structure from known and previously unreported rRNA gene sequences. An implementation of the method is freely available at https://github.com/csmiller/EMIRGE.
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spelling pubmed-32199672011-11-18 EMIRGE: reconstruction of full-length ribosomal genes from microbial community short read sequencing data Miller, Christopher S Baker, Brett J Thomas, Brian C Singer, Steven W Banfield, Jillian F Genome Biol Method Recovery of ribosomal small subunit genes by assembly of short read community DNA sequence data generally fails, making taxonomic characterization difficult. Here, we solve this problem with a novel iterative method, based on the expectation maximization algorithm, that reconstructs full-length small subunit gene sequences and provides estimates of relative taxon abundances. We apply the method to natural and simulated microbial communities, and correctly recover community structure from known and previously unreported rRNA gene sequences. An implementation of the method is freely available at https://github.com/csmiller/EMIRGE. BioMed Central 2011 2011-05-19 /pmc/articles/PMC3219967/ /pubmed/21595876 http://dx.doi.org/10.1186/gb-2011-12-5-r44 Text en Copyright ©2011 Miller et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Method
Miller, Christopher S
Baker, Brett J
Thomas, Brian C
Singer, Steven W
Banfield, Jillian F
EMIRGE: reconstruction of full-length ribosomal genes from microbial community short read sequencing data
title EMIRGE: reconstruction of full-length ribosomal genes from microbial community short read sequencing data
title_full EMIRGE: reconstruction of full-length ribosomal genes from microbial community short read sequencing data
title_fullStr EMIRGE: reconstruction of full-length ribosomal genes from microbial community short read sequencing data
title_full_unstemmed EMIRGE: reconstruction of full-length ribosomal genes from microbial community short read sequencing data
title_short EMIRGE: reconstruction of full-length ribosomal genes from microbial community short read sequencing data
title_sort emirge: reconstruction of full-length ribosomal genes from microbial community short read sequencing data
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3219967/
https://www.ncbi.nlm.nih.gov/pubmed/21595876
http://dx.doi.org/10.1186/gb-2011-12-5-r44
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