Dynamic assessment of microbial ecology (DAME): a web app for interactive analysis and visualization of microbial sequencing data

Bioinformatics
Brian D PiccoloKartik Shankar

Abstract

Dynamic assessment of microbial ecology (DAME) is a Shiny-based web application for interactive analysis and visualization of microbial sequencing data. DAME provides researchers not familiar with R programming the ability to access the most current R functions utilized for ecology and gene sequencing data analyses. Currently, DAME supports group comparisons of several ecological estimates of α-diversity and β-diversity, along with differential abundance analysis of individual taxa. Using the Shiny framework, the user has complete control of all aspects of the data analysis, including sample/experimental group selection and filtering, estimate selection, statistical methods and visualization parameters. Furthermore, graphical and tabular outputs are supported by R packages using D3.js and are fully interactive. DAME was implemented in R but can be modified by Hypertext Markup Language (HTML), Cascading Style Sheets (CSS), and JavaScript. It is freely available on the web at https://acnc-shinyapps.shinyapps.io/DAME/. Local installation and source code are available through Github (https://github.com/bdpiccolo/ACNC-DAME). Any system with R can launch DAME locally provided the shiny package is installed. bdpiccolo@uams.edu.

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Citations

Jul 16, 2020·Interdisciplinary Sciences, Computational Life Sciences·Sufang WangHui Yang
Sep 25, 2018·The Journal of Nutrition·John J MiklavcicLaxmi Yeruva
Dec 30, 2020·Journal of Animal Science·Rachel J SorensenJames M Lattimer
Feb 17, 2019·The Journal of Nutritional Biochemistry·Chrissa PetersenPon Velayutham Anandh Babu
Jan 31, 2021·Journal of Animal Science·Rachel J SorensenJames M Lattimer
Aug 12, 2021·Journal of Animal Science·Rachel J SorensenJames M Lattimer

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