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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...

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Detalles Bibliográficos
Autores principales: Sanchez, Christopher D, Brown, J Benjamin, Gal-Oz, Omree, Singer, Esther
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
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.
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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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