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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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 |
work_keys_str_mv |
AT himelmallick experimentaldesignandquantitativeanalysisofmicrobialcommunitymultiomics AT siyuanma experimentaldesignandquantitativeanalysisofmicrobialcommunitymultiomics AT ericafranzosa experimentaldesignandquantitativeanalysisofmicrobialcommunitymultiomics AT tommivatanen experimentaldesignandquantitativeanalysisofmicrobialcommunitymultiomics AT xochitlcmorgan experimentaldesignandquantitativeanalysisofmicrobialcommunitymultiomics AT curtishuttenhower experimentaldesignandquantitativeanalysisofmicrobialcommunitymultiomics |
_version_ |
1725624398635859968 |