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Dynamic assessment of microbial ecology (DAME): a web app for interactive analysis and visualization of microbial sequencing data.
Piccolo, Brian D; Wankhade, Umesh D; Chintapalli, Sree V; Bhattacharyya, Sudeepa; Chunqiao, Luo; Shankar, Kartik.
Afiliação
  • Piccolo BD; Arkansas Children's Nutrition Center, Little Rock, AR 72202, USA.
  • Wankhade UD; Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR 72202, USA.
  • Chintapalli SV; Arkansas Children's Nutrition Center, Little Rock, AR 72202, USA.
  • Bhattacharyya S; Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR 72202, USA.
  • Chunqiao L; Arkansas Children's Nutrition Center, Little Rock, AR 72202, USA.
  • Shankar K; Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR 72202, USA.
Bioinformatics ; 34(6): 1050-1052, 2018 03 15.
Article em En | MEDLINE | ID: mdl-29087435
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 ß-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. Contact: bdpiccolo@uams.edu.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Interpretação Estatística de Dados / Ecossistema Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Interpretação Estatística de Dados / Ecossistema Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos