Multi-omic modelling of inflammatory bowel disease with regularized canonical correlation analysis

Personalized medicine requires finding relationships between variables that influence a patient's phenotype and predicting an outcome. Sparse generalized canonical correlation analysis identifies relationships between different groups of variables. This method requires establishing a model of t...

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Detalhes bibliográficos
Autores: Revilla, Lluís, Mayorgas, Aida, Corraliza Márquez, Ana Maria, Masamunt, Maria Carme, Metwaly, Amira, Haller, Dirk, Tristán, Eva, Carrasco García, Anna, Esteve i Comas, Maria, Panés Díaz, Julià, Ricart, Elena, Lozano Salvatella, Juan José, Salas Martínez, Azucena
Tipo de documento: artigo
Estado:Versão publicada
Data de publicação:2021
País:España
Recursos:Universidad de Barcelona
Repositório:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/194949
Acesso em linha:https://hdl.handle.net/2445/194949
Access Level:Acceso aberto
Palavra-chave:Transcripció genètica
Microbiota intestinal
Glioma
Hematopoesi
Genetic transcription
Gastrointestinal microbiome
Gliomas
Hematopoiesis
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repository_id_str
spelling Multi-omic modelling of inflammatory bowel disease with regularized canonical correlation analysisRevilla, LluísMayorgas, AidaCorraliza Márquez, Ana MariaMasamunt, Maria CarmeMetwaly, AmiraHaller, DirkTristán, EvaCarrasco García, AnnaEsteve i Comas, MariaPanés Díaz, JuliàRicart, ElenaLozano Salvatella, Juan JoséSalas Martínez, AzucenaTranscripció genèticaMicrobiota intestinalGliomaHematopoesiGenetic transcriptionGastrointestinal microbiomeGliomasHematopoiesisPersonalized medicine requires finding relationships between variables that influence a patient's phenotype and predicting an outcome. Sparse generalized canonical correlation analysis identifies relationships between different groups of variables. This method requires establishing a model of the expected interaction between those variables. Describing these interactions is challenging when the relationship is unknown or when there is no pre-established hypothesis. Thus, our aim was to develop a method to find the relationships between microbiome and host transcriptome data and the relevant clinical variables in a complex disease, such as Crohn's disease.Public Library of Science (PLoS)2021info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/2445/194949Articles publicats en revistes (IDIBAPS: Institut d'investigacions Biomèdiques August Pi i Sunyer)reponame:Dipòsit Digital de la UBinstname:Universidad de BarcelonaInglésReproducció del document publicat a: https://doi.org/10.1371/journal.pone.0246367PLoS One, 2021, vol. 16, num. 2, p. e0246367https://doi.org/10.1371/journal.pone.0246367cc-by (c) Revilla, Lluís et al., 2021https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:diposit.ub.edu:2445/1949492026-05-27T06:46:51Z
dc.title.none.fl_str_mv Multi-omic modelling of inflammatory bowel disease with regularized canonical correlation analysis
title Multi-omic modelling of inflammatory bowel disease with regularized canonical correlation analysis
spellingShingle Multi-omic modelling of inflammatory bowel disease with regularized canonical correlation analysis
Revilla, Lluís
Transcripció genètica
Microbiota intestinal
Glioma
Hematopoesi
Genetic transcription
Gastrointestinal microbiome
Gliomas
Hematopoiesis
title_short Multi-omic modelling of inflammatory bowel disease with regularized canonical correlation analysis
title_full Multi-omic modelling of inflammatory bowel disease with regularized canonical correlation analysis
title_fullStr Multi-omic modelling of inflammatory bowel disease with regularized canonical correlation analysis
title_full_unstemmed Multi-omic modelling of inflammatory bowel disease with regularized canonical correlation analysis
title_sort Multi-omic modelling of inflammatory bowel disease with regularized canonical correlation analysis
dc.creator.none.fl_str_mv Revilla, Lluís
Mayorgas, Aida
Corraliza Márquez, Ana Maria
Masamunt, Maria Carme
Metwaly, Amira
Haller, Dirk
Tristán, Eva
Carrasco García, Anna
Esteve i Comas, Maria
Panés Díaz, Julià
Ricart, Elena
Lozano Salvatella, Juan José
Salas Martínez, Azucena
author Revilla, Lluís
author_facet Revilla, Lluís
Mayorgas, Aida
Corraliza Márquez, Ana Maria
Masamunt, Maria Carme
Metwaly, Amira
Haller, Dirk
Tristán, Eva
Carrasco García, Anna
Esteve i Comas, Maria
Panés Díaz, Julià
Ricart, Elena
Lozano Salvatella, Juan José
Salas Martínez, Azucena
author_role author
author2 Mayorgas, Aida
Corraliza Márquez, Ana Maria
Masamunt, Maria Carme
Metwaly, Amira
Haller, Dirk
Tristán, Eva
Carrasco García, Anna
Esteve i Comas, Maria
Panés Díaz, Julià
Ricart, Elena
Lozano Salvatella, Juan José
Salas Martínez, Azucena
author2_role author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Transcripció genètica
Microbiota intestinal
Glioma
Hematopoesi
Genetic transcription
Gastrointestinal microbiome
Gliomas
Hematopoiesis
topic Transcripció genètica
Microbiota intestinal
Glioma
Hematopoesi
Genetic transcription
Gastrointestinal microbiome
Gliomas
Hematopoiesis
description Personalized medicine requires finding relationships between variables that influence a patient's phenotype and predicting an outcome. Sparse generalized canonical correlation analysis identifies relationships between different groups of variables. This method requires establishing a model of the expected interaction between those variables. Describing these interactions is challenging when the relationship is unknown or when there is no pre-established hypothesis. Thus, our aim was to develop a method to find the relationships between microbiome and host transcriptome data and the relevant clinical variables in a complex disease, such as Crohn's disease.
publishDate 2021
dc.date.none.fl_str_mv 2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/194949
url https://hdl.handle.net/2445/194949
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.1371/journal.pone.0246367
PLoS One, 2021, vol. 16, num. 2, p. e0246367
https://doi.org/10.1371/journal.pone.0246367
dc.rights.none.fl_str_mv cc-by (c) Revilla, Lluís et al., 2021
https://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc-by (c) Revilla, Lluís et al., 2021
https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Public Library of Science (PLoS)
publisher.none.fl_str_mv Public Library of Science (PLoS)
dc.source.none.fl_str_mv Articles publicats en revistes (IDIBAPS: Institut d'investigacions Biomèdiques August Pi i Sunyer)
reponame:Dipòsit Digital de la UB
instname:Universidad de Barcelona
instname_str Universidad de Barcelona
reponame_str Dipòsit Digital de la UB
collection Dipòsit Digital de la UB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.300724

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