Work Description

Title: Transmission of Oral microbiome and Sequencing - Symptom and Shedding Duration Open Access Deposited

h
Attribute Value
Methodology
  • Index cases of influenza were identified at a major healthcare facility in Managua, Nicaragua. Index cases and their family members were enrolled for follow up and with nose/throat samples collected at 2-3 day intervals for up to 13 days. Sociodemographic and household data were collected at enrollment. 16S rRNA sequencing of the V4 region (Illumina MiSeq V2 chemistry 2x250--Illumina, San Diego, CA) was conducted at the University of Michigan Microbial Systems Laboratories on samples collected at enrollment and at the last day of follow up. Accelerated failure time models were used to examine the role of the nose/throat microbiome on symptom duration, shedding duration, and time to infection. For a full description of methodology, please see the associated publication.
Description
  • Data include variables used to run accelerated failure time models examining the association between the nose/throat microbiome and 1) symptom duration, 2) shedding duration, and 3) time to infection. Certain individual participant data have been excluded due to identifiability concerns. Data also include the oligotype count table and taxonomic classifications.
Creator
Depositor
  • kyuhan@umich.edu
Contact information
Discipline
Funding agency
  • National Institutes of Health (NIH)
Keyword
Citations to related material
Resource type
Last modified
  • 04/22/2020
Published
  • 10/05/2018
Language
DOI
  • https://doi.org/10.7302/Z2W66J18
License
To Cite this Work:
Lee, K. H. (2018). Transmission of Oral microbiome and Sequencing - Symptom and Shedding Duration [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/Z2W66J18

Relationships

In Collection:

Files (Count: 11; Size: 891 KB)

Download All Files (To download individual files, select them in the “Files” panel above)

Best for data sets < 3 GB. Downloads all files plus metadata into a zip file.



Best for data sets > 3 GB. Globus is the platform Deep Blue Data uses to make large data sets available.   More about Globus

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.