Seed: a user-friendly tool for exploring and visualizing microbial community data

Summary: In this article we present Simple Exploration of Ecological Data (Seed), a data exploration tool for microbial communities. Seed is written in R using the Shiny library. This provides access to powerful R-based functions and libraries through a simple user interface. Seed allows users to ex...

Descripción completa

Detalles Bibliográficos
Autores principales: Beck, Daniel, Dennis, Christopher, Foster, James A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2015
Materias:
Applications Notes
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4325548/
https://www.ncbi.nlm.nih.gov/pubmed/25332377
http://dx.doi.org/10.1093/bioinformatics/btu693
_version_ 1782356824550277120
author Beck, Daniel
Dennis, Christopher
Foster, James A.
author_facet Beck, Daniel
Dennis, Christopher
Foster, James A.
author_sort Beck, Daniel
collection PubMed
description Summary: In this article we present Simple Exploration of Ecological Data (Seed), a data exploration tool for microbial communities. Seed is written in R using the Shiny library. This provides access to powerful R-based functions and libraries through a simple user interface. Seed allows users to explore ecological datasets using principal coordinate analyses, scatter plots, bar plots, hierarchal clustering and heatmaps. Availability and implementation: Seed is open source and available at https://github.com/danlbek/Seed. Contact: danlbek@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.
format Online
Article
Text
id pubmed-4325548
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-43255482015-03-02 Seed: a user-friendly tool for exploring and visualizing microbial community data Beck, Daniel Dennis, Christopher Foster, James A. Bioinformatics Applications Notes Summary: In this article we present Simple Exploration of Ecological Data (Seed), a data exploration tool for microbial communities. Seed is written in R using the Shiny library. This provides access to powerful R-based functions and libraries through a simple user interface. Seed allows users to explore ecological datasets using principal coordinate analyses, scatter plots, bar plots, hierarchal clustering and heatmaps. Availability and implementation: Seed is open source and available at https://github.com/danlbek/Seed. Contact: danlbek@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2015-02-15 2014-10-20 /pmc/articles/PMC4325548/ /pubmed/25332377 http://dx.doi.org/10.1093/bioinformatics/btu693 Text en © The Author 2014. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Beck, Daniel
Dennis, Christopher
Foster, James A.
Seed: a user-friendly tool for exploring and visualizing microbial community data
title Seed: a user-friendly tool for exploring and visualizing microbial community data
title_full Seed: a user-friendly tool for exploring and visualizing microbial community data
title_fullStr Seed: a user-friendly tool for exploring and visualizing microbial community data
title_full_unstemmed Seed: a user-friendly tool for exploring and visualizing microbial community data
title_short Seed: a user-friendly tool for exploring and visualizing microbial community data
title_sort seed: a user-friendly tool for exploring and visualizing microbial community data
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4325548/
https://www.ncbi.nlm.nih.gov/pubmed/25332377
http://dx.doi.org/10.1093/bioinformatics/btu693
work_keys_str_mv AT beckdaniel seedauserfriendlytoolforexploringandvisualizingmicrobialcommunitydata
AT dennischristopher seedauserfriendlytoolforexploringandvisualizingmicrobialcommunitydata
AT fosterjamesa seedauserfriendlytoolforexploringandvisualizingmicrobialcommunitydata

Ejemplares similares