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dc.contributor.authorWagner, Justin
dc.contributor.authorKancherla, Jayaram
dc.contributor.authorBraccia, Domenick
dc.contributor.authorMatsumara, James
dc.contributor.authorFelix, Victor
dc.contributor.authorCrabtree, Jonathan
dc.contributor.authorMahurkar, Anup
dc.contributor.authorCorrada Bravo, Héctor
dc.date.accessioned2020-08-04T17:54:53Z
dc.date.available2020-08-04T17:54:53Z
dc.date.issued2020-06-12
dc.identifier.urihttp://hdl.handle.net/10713/13464
dc.description.abstractThe rich data produced by the second phase of the Human Microbiome Project (iHMP) offers a unique opportunity to test hypotheses that interactions between microbial communities and a human host might impact an individual's health or disease status. In this work we describe infrastructure that integrates Metaviz, an interactive microbiome data analysis and visualization tool, with the iHMP Data Coordination Center web portal and the HMP2Data R/Bioconductor package. We describe integrative statistical and visual analyses of two datasets from iHMP using Metaviz along with the metagenomeSeq R/Bioconductor package for statistical analysis of differential abundance analysis. These use cases demonstrate the utility of a combined approach to access and analyze data from this resource. © 2020 Wagner J et al.en_US
dc.description.sponsorshipNational Institutes of Healthen_US
dc.description.urihttps://doi.org/10.12688/f1000research.24345.1en_US
dc.language.isoen_USen_US
dc.publisherF1000 Research Ltden_US
dc.relation.ispartofF1000Researchen_US
dc.rightsThis is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectIntegrative Human Microbiome Projecten_US
dc.subjectmetagenomicsen_US
dc.subjectR/Bioconductoren_US
dc.subjectvisualizationen_US
dc.titleInteractive exploratory data analysis of Integrative Human Microbiome Project data using Metavizen_US
dc.typeArticleen_US
dc.identifier.doi10.12688/f1000research.24345.1
dc.source.volume9
dc.source.beginpage601


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This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's license is described as This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.