Balances: a new perspective for microbiome analysis

High-throughput sequencing technologies have revolutionized microbiome research by allowing the relative quantification of microbiome composition and function in different environments. In this work we focus on the identification of microbial signatures, groups of microbial taxa that are predictive...

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Detalles Bibliográficos
Autores: Rivera Pinto, J., Egozcue Rubí, Juan José|||0000-0002-5144-4483, Pawlowsky Glahn, Vera, Paredes, Raul, Noguera Julian, Marc, Calle, M. L.
Tipo de recurso: artículo
Fecha de publicación:2018
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/126846
Acceso en línea:https://hdl.handle.net/2117/126846
https://dx.doi.org/10.1128/mSystems.00053-18
Access Level:acceso abierto
Palabra clave:Microbiota
balances
compositional data
microbiome
Microorganismes
Àrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciències
Àrees temàtiques de la UPC::Ciències de la salut::Medicina
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oai_identifier_str oai:upcommons.upc.edu:2117/126846
network_acronym_str ES
network_name_str España
repository_id_str
spelling Balances: a new perspective for microbiome analysisRivera Pinto, J.Egozcue Rubí, Juan José|||0000-0002-5144-4483Pawlowsky Glahn, VeraParedes, RaulNoguera Julian, MarcCalle, M. L.Microbiotabalancescompositional datamicrobiomeMicroorganismesÀrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciènciesÀrees temàtiques de la UPC::Ciències de la salut::MedicinaHigh-throughput sequencing technologies have revolutionized microbiome research by allowing the relative quantification of microbiome composition and function in different environments. In this work we focus on the identification of microbial signatures, groups of microbial taxa that are predictive of a phenotype of interest. We do this by acknowledging the compositional nature of the microbiome and the fact that it carries relative information. Thus, instead of defining a microbial signature as a linear combination in real space corresponding to the abundances of a group of taxa, we consider microbial signatures given by the geometric means of data from two groups of taxa whose relative abundances, or balance, are associated with the response variable of interest. In this work we present selbal, a greedy stepwise algorithm for selection of balances or microbial signatures that preserves the principles of compositional data analysis. We illustrate the algorithm with 16S rRNA abundance data from a Crohn’s microbiome study and an HIV microbiome study. We propose a new algorithm for the identification of microbial signatures. These microbial signatures can be used for diagnosis, prognosis, or prediction of therapeutic response based on an individual’s specific microbiota.Peer Reviewed20182018-07-0120192019-01-15journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/126846https://dx.doi.org/10.1128/mSystems.00053-1830035234reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)InglésengMinisterio de Economía y Competitividad http://doi.org/10.13039/501100003329 MTM2015-64465-C2-1-R METODOS ESTADISTICOS PARA ENSAYOS CLINICOS, PATRONES DE CENSURA COMPLEJOS Y ANALISIS INTEGRADO DE DATOS OMICOSopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 3.0 Spainhttp://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/1268462026-05-27T15:37:01Z
dc.title.none.fl_str_mv Balances: a new perspective for microbiome analysis
title Balances: a new perspective for microbiome analysis
spellingShingle Balances: a new perspective for microbiome analysis
Rivera Pinto, J.
Microbiota
balances
compositional data
microbiome
Microorganismes
Àrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciències
Àrees temàtiques de la UPC::Ciències de la salut::Medicina
title_short Balances: a new perspective for microbiome analysis
title_full Balances: a new perspective for microbiome analysis
title_fullStr Balances: a new perspective for microbiome analysis
title_full_unstemmed Balances: a new perspective for microbiome analysis
title_sort Balances: a new perspective for microbiome analysis
dc.creator.none.fl_str_mv Rivera Pinto, J.
Egozcue Rubí, Juan José|||0000-0002-5144-4483
Pawlowsky Glahn, Vera
Paredes, Raul
Noguera Julian, Marc
Calle, M. L.
author Rivera Pinto, J.
author_facet Rivera Pinto, J.
Egozcue Rubí, Juan José|||0000-0002-5144-4483
Pawlowsky Glahn, Vera
Paredes, Raul
Noguera Julian, Marc
Calle, M. L.
author_role author
author2 Egozcue Rubí, Juan José|||0000-0002-5144-4483
Pawlowsky Glahn, Vera
Paredes, Raul
Noguera Julian, Marc
Calle, M. L.
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Microbiota
balances
compositional data
microbiome
Microorganismes
Àrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciències
Àrees temàtiques de la UPC::Ciències de la salut::Medicina
topic Microbiota
balances
compositional data
microbiome
Microorganismes
Àrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciències
Àrees temàtiques de la UPC::Ciències de la salut::Medicina
description High-throughput sequencing technologies have revolutionized microbiome research by allowing the relative quantification of microbiome composition and function in different environments. In this work we focus on the identification of microbial signatures, groups of microbial taxa that are predictive of a phenotype of interest. We do this by acknowledging the compositional nature of the microbiome and the fact that it carries relative information. Thus, instead of defining a microbial signature as a linear combination in real space corresponding to the abundances of a group of taxa, we consider microbial signatures given by the geometric means of data from two groups of taxa whose relative abundances, or balance, are associated with the response variable of interest. In this work we present selbal, a greedy stepwise algorithm for selection of balances or microbial signatures that preserves the principles of compositional data analysis. We illustrate the algorithm with 16S rRNA abundance data from a Crohn’s microbiome study and an HIV microbiome study. We propose a new algorithm for the identification of microbial signatures. These microbial signatures can be used for diagnosis, prognosis, or prediction of therapeutic response based on an individual’s specific microbiota.
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-07-01
2019
2019-01-15
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/126846
https://dx.doi.org/10.1128/mSystems.00053-18
30035234
url https://hdl.handle.net/2117/126846
https://dx.doi.org/10.1128/mSystems.00053-18
identifier_str_mv 30035234
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Ministerio de Economía y Competitividad http://doi.org/10.13039/501100003329 MTM2015-64465-C2-1-R METODOS ESTADISTICOS PARA ENSAYOS CLINICOS, PATRONES DE CENSURA COMPLEJOS Y ANALISIS INTEGRADO DE DATOS OMICOS
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 3.0 Spain
http://creativecommons.org/licenses/by/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 3.0 Spain
http://creativecommons.org/licenses/by/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300719

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