Experimental design and quantitative analysis of microbial community multiomics

Abstract Studies of the microbiome have become increasingly sophisticated, and multiple sequence-based, molecular methods as well as culture-based methods exist for population-scale microbiome profiles. To link the resulting host and microbial data types to human health, several experimental design...

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Main Authors: Himel Mallick, Siyuan Ma, Eric A. Franzosa, Tommi Vatanen, Xochitl C. Morgan, Curtis Huttenhower
Format: Article
Language:English
Published: BMC 2017-11-01
Series:Genome Biology
Online Access:http://link.springer.com/article/10.1186/s13059-017-1359-z
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spelling doaj-841cbff6e79047df8448e973a1a28c012020-11-24T23:06:00ZengBMCGenome Biology1474-760X2017-11-0118111610.1186/s13059-017-1359-zExperimental design and quantitative analysis of microbial community multiomicsHimel Mallick0Siyuan Ma1Eric A. Franzosa2Tommi Vatanen3Xochitl C. Morgan4Curtis Huttenhower5Department of Biostatistics, Harvard T.H. Chan School of Public HealthDepartment of Biostatistics, Harvard T.H. Chan School of Public HealthDepartment of Biostatistics, Harvard T.H. Chan School of Public HealthBroad Institute of MIT and HarvardDepartment of Microbiology and Immunology, The University of OtagoDepartment of Biostatistics, Harvard T.H. Chan School of Public HealthAbstract Studies of the microbiome have become increasingly sophisticated, and multiple sequence-based, molecular methods as well as culture-based methods exist for population-scale microbiome profiles. To link the resulting host and microbial data types to human health, several experimental design considerations, data analysis challenges, and statistical epidemiological approaches must be addressed. Here, we survey current best practices for experimental design in microbiome molecular epidemiology, including technologies for generating, analyzing, and integrating microbiome multiomics data. We highlight studies that have identified molecular bioactives that influence human health, and we suggest steps for scaling translational microbiome research to high-throughput target discovery across large populations.http://link.springer.com/article/10.1186/s13059-017-1359-z
collection DOAJ
language English
format Article
sources DOAJ
author Himel Mallick
Siyuan Ma
Eric A. Franzosa
Tommi Vatanen
Xochitl C. Morgan
Curtis Huttenhower
spellingShingle Himel Mallick
Siyuan Ma
Eric A. Franzosa
Tommi Vatanen
Xochitl C. Morgan
Curtis Huttenhower
Experimental design and quantitative analysis of microbial community multiomics
Genome Biology
author_facet Himel Mallick
Siyuan Ma
Eric A. Franzosa
Tommi Vatanen
Xochitl C. Morgan
Curtis Huttenhower
author_sort Himel Mallick
title Experimental design and quantitative analysis of microbial community multiomics
title_short Experimental design and quantitative analysis of microbial community multiomics
title_full Experimental design and quantitative analysis of microbial community multiomics
title_fullStr Experimental design and quantitative analysis of microbial community multiomics
title_full_unstemmed Experimental design and quantitative analysis of microbial community multiomics
title_sort experimental design and quantitative analysis of microbial community multiomics
publisher BMC
series Genome Biology
issn 1474-760X
publishDate 2017-11-01
description Abstract Studies of the microbiome have become increasingly sophisticated, and multiple sequence-based, molecular methods as well as culture-based methods exist for population-scale microbiome profiles. To link the resulting host and microbial data types to human health, several experimental design considerations, data analysis challenges, and statistical epidemiological approaches must be addressed. Here, we survey current best practices for experimental design in microbiome molecular epidemiology, including technologies for generating, analyzing, and integrating microbiome multiomics data. We highlight studies that have identified molecular bioactives that influence human health, and we suggest steps for scaling translational microbiome research to high-throughput target discovery across large populations.
url http://link.springer.com/article/10.1186/s13059-017-1359-z
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AT curtishuttenhower experimentaldesignandquantitativeanalysisofmicrobialcommunitymultiomics
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