Microbiotyping the Sinonasal Microbiome

Microbiotyping the Sinonasal Microbiome

This study offers a novel description of the sinonasal microbiome, through an unsupervised machine learning approach combining dimensionality reduction and clustering. We apply our method to the International Sinonasal Microbiome Study (ISMS) dataset of 410 sinus swab samples. We propose three main...

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Bibliographic Details
Main Authors: Ahmed Bassiouni, Sathish Paramasivan, Arron Shiffer, Matthew R. Dillon, Emily K. Cope, Clare Cooksley, Mahnaz Ramezanpour, Sophia Moraitis, Mohammad Javed Ali, Benjamin S. Bleier, Claudio Callejas, Marjolein E. Cornet, Richard G. Douglas, Daniel Dutra, Christos Georgalas, Richard J. Harvey, Peter H. Hwang, Amber U. Luong, Rodney J. Schlosser, Pongsakorn Tantilipikorn, Marc A. Tewfik, Sarah Vreugde, Peter-John Wormald, J. Gregory Caporaso, Alkis J. Psaltis
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-04-01
Series:Frontiers in Cellular and Infection Microbiology
Subjects:
microbiome
sinus
next-generation sequencing
16S rRNA gene
chronic rhinosinusitis
microbiotype
Online Access:https://www.frontiersin.org/article/10.3389/fcimb.2020.00137/full

Internet

https://www.frontiersin.org/article/10.3389/fcimb.2020.00137/full

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