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EcoPLOT: dynamic analysis of biogeochemical data
MOTIVATION: We have created EcoPLOT (parameterized linkage of omics-driven technologies), a web-app for the dynamic, interactive analysis of biogeochemical datasets that combines state-of-the-art analysis tools to statistically and graphically explore environmental, geochemical and microbiome datase...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8825466/ https://www.ncbi.nlm.nih.gov/pubmed/34927685 http://dx.doi.org/10.1093/bioinformatics/btab842 |
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author | Sanchez, Christopher D Brown, J Benjamin Gal-Oz, Omree Singer, Esther |
author_facet | Sanchez, Christopher D Brown, J Benjamin Gal-Oz, Omree Singer, Esther |
author_sort | Sanchez, Christopher D |
collection | PubMed |
description | MOTIVATION: We have created EcoPLOT (parameterized linkage of omics-driven technologies), a web-app for the dynamic, interactive analysis of biogeochemical datasets that combines state-of-the-art analysis tools to statistically and graphically explore environmental, geochemical and microbiome datasets. Using the iterative random forest, a machine learning algorithm, EcoPLOT allows for the de novo discovery of drivers which exhibit significant impact on plant, microbial or soil dynamics. AVAILABILITY AND IMPLEMENTATION: EcoPLOT is built entirely within the R language. It can be accessed through any system where R is installed, including Windows, Mac and most Linux systems. EcoPLOT is free to use and can be accessed at https://github.com/cdsanchez18/EcoPLOT. |
format | Online Article Text |
id | pubmed-8825466 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-88254662022-02-09 EcoPLOT: dynamic analysis of biogeochemical data Sanchez, Christopher D Brown, J Benjamin Gal-Oz, Omree Singer, Esther Bioinformatics Applications Notes MOTIVATION: We have created EcoPLOT (parameterized linkage of omics-driven technologies), a web-app for the dynamic, interactive analysis of biogeochemical datasets that combines state-of-the-art analysis tools to statistically and graphically explore environmental, geochemical and microbiome datasets. Using the iterative random forest, a machine learning algorithm, EcoPLOT allows for the de novo discovery of drivers which exhibit significant impact on plant, microbial or soil dynamics. AVAILABILITY AND IMPLEMENTATION: EcoPLOT is built entirely within the R language. It can be accessed through any system where R is installed, including Windows, Mac and most Linux systems. EcoPLOT is free to use and can be accessed at https://github.com/cdsanchez18/EcoPLOT. Oxford University Press 2021-12-20 /pmc/articles/PMC8825466/ /pubmed/34927685 http://dx.doi.org/10.1093/bioinformatics/btab842 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Applications Notes Sanchez, Christopher D Brown, J Benjamin Gal-Oz, Omree Singer, Esther EcoPLOT: dynamic analysis of biogeochemical data |
title | EcoPLOT: dynamic analysis of biogeochemical data |
title_full | EcoPLOT: dynamic analysis of biogeochemical data |
title_fullStr | EcoPLOT: dynamic analysis of biogeochemical data |
title_full_unstemmed | EcoPLOT: dynamic analysis of biogeochemical data |
title_short | EcoPLOT: dynamic analysis of biogeochemical data |
title_sort | ecoplot: dynamic analysis of biogeochemical data |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8825466/ https://www.ncbi.nlm.nih.gov/pubmed/34927685 http://dx.doi.org/10.1093/bioinformatics/btab842 |
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