Easy16S is designed to facilitate the exploration, visualization, and analysis of microbiome data.
The goal of easy16S is to provide a user-friendly interactive web-application with convenient functions and default settings to explore, visualize and analyze metabarcoding data.
It builds upon the phyloseq package and its extensions and is tightly integrated with the FROGS sequence processing suite.
Easy16S can be accessed directly via an online instance: https://shiny.migale.inrae.fr/app/easy16S.
Installation
You can install the development version of easy16S like so:
# install.packages("remotes")
remotes::install_gitlab(
repo = "migale/easy16S@main",
host = "forgemia.inra.fr"
)
Run the Shiny Application
To run the Shiny application, execute the following code in your R environment:
Docker Integration
For each release, a CI/CD pipeline builds a Docker image using a Dockerfile. This process is particularly useful for deploying with ShinyProxy.
The Docker images are available in the container registry.
The image exposes port 3838
and launches the app using easy16S::run_app(options = list(launch.browser = FALSE))
Therefore, to run the application, execute the following commands:
docker pull registry.forgemia.inra.fr/migale/easy16s:v24.07
docker run --rm --publish 3838:3838 registry.forgemia.inra.fr/migale/easy16s:v24.07
The app will be accessible at http://localhost:3838/.
Disclaimer
Easy16S facilitates the exploration, visualization, and analysis of metabarcoding data with ease. However, users should be cautious about over-interpreting the results. Proper interpretation of metagenomics data requires a solid understanding of microbial ecology, biostatistics, and the specific field of study. While our tool is designed to be user-friendly, the complexity of metagenomics data analysis means that the results can be misleading if not carefully evaluated.
We have incorporated several default settings and guardrails to guide users and reduce the risk of misuse. However, if you lack a background in metagenomics, it is highly advisable to collaborate with bioinformaticians and biostatisticians to ensure robust and reliable conclusions from your work.
FAQ
It is called easy”16S”. Can I use it with another marker?
Yes! Easy16S is the historical name. This tool was originally developed for 16S amplicon data. This is why the “16S” has remained in the name. It can also be used to analyze other metagenomics data such as ITS or MAGs. However, care must be taken with the interpretations made, and results must not be over-interpreted.
Issues and Support
If you encounter any bugs or have suggestions for improvement, please use the issue tracker.
Cite us
If you use easy16S
in your research or applications, please cite the associated publication in Journal of Open Source Software : .
Midoux et al., (2024). Easy16S: a user-friendly Shiny web-service for exploration and visualization of microbiome data. Journal of Open Source Software, 9(103), 6704, https://doi.org/10.21105/joss.06704
@article{easy16S,
title = {Easy16S: a user-friendly Shiny web-service for exploration and
visualization of microbiome data.},
author = {Cédric Midoux and Olivier Rué and Olivier Chapleur and Ariane Bize and Valentin Loux and Mahendra Mariadassou},
journal = {Journal of Open Source Software},
publisher = {The Open Journal},
year = {2024},
volume = {9},
number = {103},
pages = {6704},
doi = {10.21105/joss.06704},
issn = {2475-9066},
url = {https://easy16s.migale.inrae.fr},
}
If you used the online version, we also appreciate acknowledgment from research teams using computing resources. Please include the following sentence in the publications of your analyses:
We are grateful to the INRAE MIGALE bioinformatics facility (MIGALE, INRAE, 2020. Migale bioinformatics Facility, doi: 10.15454/1.5572390655343293E12) for providing help and computing resources.
Code of Conduct
Please note that the easy16S project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.