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

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Abstract Summary 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. Availability and implementation 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.
Title: Dynamic assessment of microbial ecology (DAME): a web app for interactive analysis and visualization of microbial sequencing data
Description:
Abstract Summary 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.
Availability and implementation 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.

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