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ARS Home » Southeast Area » Little Rock, Arkansas » Microbiome and Metabolism Research Unit » Research » Publications at this Location » Publication #341424
Title: Dynamic assessment of microbial ecology (DAME): A shiny app for analysis and visualization of microbial sequencing data

Author
item PICCOLO, BRIAN - Arkansas Children'S Nutrition Research Center (ACNC)
item WANKHADE, UMESH - Arkansas Children'S Nutrition Research Center (ACNC)
item CHINTAPALLI, SREE - Arkansas Children'S Nutrition Research Center (ACNC)
item SHANKAR, KARTIK - Arkansas Children'S Nutrition Research Center (ACNC)

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 5/1/2017
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: A new renaissance in knowledge about the role of commensal microbiota in health and disease is well underway facilitated by culture-independent sequencing technologies; however, microbial sequencing data poses new challenges (e.g., taxonomic hierarchy, overdispersion) not generally seen in more traditional sequencing outputs. Additionally, complex study paradigms from clinical or basic research studies necessitate a multilayered analysis pipeline that can seamlessly integrate both primary bioinformatics and secondary statistical analysis combined with data visualization. In order to address this need, we created a web-based Shiny app, titled DAME, which allows users not familiar with R programming to import, filter, and analyze microbial sequencing data from experimental studies. DAME only requires two files (a BIOM file with sequencing reads combined with taxonomy details, and a csv file containing experimental metadata), which upon upload will trigger the app to render a linear work-flow controlled by the user. Currently, DAME supports group comparisons of several ecological estimates of a-diversity (ANOVA) and B-diversity indices (ordinations and PERMANOVA). Additionally, pairwise differential comparisons of operational taxonomic units (OTUs) using Negative Binomial Regression at all taxonomic levels can be performed. All analyses are accompanied by dynamic graphics and tables for complete user interactivity. DAME leverages functions derived from phyloseq, vegan, and DESeq2 packages for microbial data organization and analysis and DT, highcharter* and scatterD3 for table and plot visualizations.