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Challenges of Microbiome Data Analysis in Chronic Respiratory Disease Studies: Examples from Three French Studies

dc.rights.licenseopenen_US
hal.structure.identifierStatistics In System biology and Translational Medicine [SISTM]
hal.structure.identifierBordeaux population health [BPH]
hal.structure.identifierCentre Inria de l'Université de Bordeaux
hal.structure.identifierUniversité de Bordeaux [UB]
dc.contributor.authorAVALOS, Marta
hal.structure.identifierUniversidad de Valparaiso = Valparaiso University
dc.contributor.authorBARRERA, John
hal.structure.identifierUniversidad de Valparaiso = Valparaiso University
dc.contributor.authorMEZA, Cristian
hal.structure.identifierUniversidad Adolfo Ibáñez = University Adolfo Ibañez [Santiago]
dc.contributor.authorEYHERAMENDY, Susana
hal.structure.identifierGenoscreen [Lille]
dc.contributor.authorVANDENBORGHT, Louise-Eva
hal.structure.identifierCentre de recherche Cardio-Thoracique de Bordeaux [Bordeaux] [CRCTB]
hal.structure.identifierUniversité de Bordeaux [UB]
hal.structure.identifierCHU de Bordeaux Pellegrin [Bordeaux]
dc.contributor.authorENAUD, Raphaël
hal.structure.identifierUniversité de Bordeaux [UB]
hal.structure.identifierCHU de Bordeaux Pellegrin [Bordeaux]
hal.structure.identifierCentre de recherche Cardio-Thoracique de Bordeaux [Bordeaux] [CRCTB]
dc.contributor.authorDELHAES, Laurence
dc.date.accessioned2025-06-17T08:48:21Z
dc.date.available2025-06-17T08:48:21Z
dc.date.conference2024-12-16
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/206933
dc.description.abstractEnStudies on chronic respiratory diseases and their associations with the microbiome -whether from the respiratory tract, gut (gut-lung axis), or environmental sources (e.g., indoor dust)- present unique statistical challenges. These studies often involve small sample sizes and high-dimensional data, with hundreds or thousands of bacterial and fungal abundances measured. The data are compositional, frequently zero-inflated, and either geographically grouped (e.g., environmental microbiome and asthma in the COBRA-Env study) or longitudinal (e.g., cystic fibrosis patients in the French LumIvaBiota cohort).Meta-analysis is an essential tool for synthesizing knowledge by pooling data from multiple studies to increase statistical power. However, microbiome research often shows high variability across studies in terms of methodologies, sample collection, sequencing techniques, and population characteristics. Exploring the sources of heterogeneity is crucial for ensuring comparability. Penalized meta-regression methods, such as the Lasso, provide a way to address heterogeneity in cases with few studies (such as those on chronic respiratory diseases linked to the microbiome) and many potential explanatory factors.In this talk, we will illustrate the statistical challenges associated with microbiome studies in chronic respiratory diseases and discuss strategies to address these complexities.
dc.language.isoENen_US
dc.rights.urihttp://creativecommons.org/licenses/by/
dc.subject.enBiostatistics
dc.subject.enMachine Learning
dc.subject.enHigh-dimensional
dc.subject.enApplication
dc.subject.enComputation
dc.title.enChallenges of Microbiome Data Analysis in Chronic Respiratory Disease Studies: Examples from Three French Studies
dc.typeCommunication dans un congrèsen_US
dc.subject.halMathématiques [math]/Statistiques [math.ST]en_US
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
bordeaux.hal.laboratoriesCentre de Recherche Cardio-Thoracique de Bordeaux (CRCTB) - U1045en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionINSERMen_US
bordeaux.conference.titleICSDS 2024 - International Conference on Statistics and Data Scienceen_US
bordeaux.countryfren_US
bordeaux.conference.cityNiceen_US
bordeaux.import.sourcehal
hal.identifierhal-04846596
hal.version1
hal.invitedouien_US
hal.proceedingsnonen_US
hal.conference.organizerInstitute of Mathematical Statistics (IMS)en_US
hal.conference.end2024-12-19
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exportfalse
workflow.import.sourcehal
dc.rights.ccPas de Licence CCen_US
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.au=AVALOS,%20Marta&BARRERA,%20John&MEZA,%20Cristian&EYHERAMENDY,%20Susana&VANDENBORGHT,%20Louise-Eva&rft.genre=unknown


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