SOFTWARE INFRASTRUCTURE FOR VISUAL AND INTEGRATIVE ANALYSIS OF MICROBIOME DATA

dc.contributor.advisorCorrada Bravo, Hectoren_US
dc.contributor.authorWagner, Justinen_US
dc.contributor.departmentComputer Scienceen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2018-09-07T05:37:08Z
dc.date.available2018-09-07T05:37:08Z
dc.date.issued2018en_US
dc.description.abstractMicrobiome sequencing allows researchers to reconstruct bacterial community census profiles at resolutions greater than previous methodologies. As a result, increasingly large numbers of these taxonomic community profiles are now generated, analyzed, and published by researchers in the field. In this work, I present new methods and software infrastructure for visualization and sharing of microbiome data. The overall goal is to enable a researcher to complete cycles of exploratory and confirmatory analysis over metagenomic data. I describe Metaviz, an interactive statistical and visual analysis tool specifically designed for effective taxonomic hierarchy navigation and data analysis feature selection. I next detail the incorporation of Metaviz into the Human Microbiome Project Data Portal. I then show a novel method to visualize longitudinal data across multiple features built as an extension over Metaviz. Finally, previous work has shown that specific subjects in an experimental cohort can be identified using their microbiome data. I developed software using a secure multi-party computation library to complete comparative analyses of metagenomic data across cohorts without directly revealing feature count values for individuals.en_US
dc.identifierhttps://doi.org/10.13016/M2GX44Z1H
dc.identifier.urihttp://hdl.handle.net/1903/21141
dc.language.isoenen_US
dc.subject.pqcontrolledComputer scienceen_US
dc.subject.pquncontrolledInfrastructureen_US
dc.subject.pquncontrolledMicrobiomeen_US
dc.subject.pquncontrolledVisualizationen_US
dc.titleSOFTWARE INFRASTRUCTURE FOR VISUAL AND INTEGRATIVE ANALYSIS OF MICROBIOME DATAen_US
dc.typeDissertationen_US

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