Eco-Flow is a UCL based research initiative to develop agri-ecology specific modern, reproducible and scalable data pipelines.
Eco-Flow wants to do more than just build pipelines, we want to cultivate a healthy community of people who share similar research within agri-ecology who can help support each other with their research and analysis.
This community is centered around the pipelines developed by the Eco-Flow team. The pipelines developed will be requested by the community.
If you would like to join the community then please email ecoflowucl [at] gmail.com.
Or start a community discussion about a potential pipeline by creating a new issue on Eco-Flow/pipeline-discussions.
Chris is a senior bioinformatician on the project, with a background in omic technologies and pipeline development.
Professor Seirian Sumner is a leading researcher in ecology and genomics.
Professor Yannick Wurm is a data scientist expert on genome analysis and evolution.
Simon is a senior bioinformatician on the project, with a background in pipeline development and containerisation.
Simon moved to Genomics England (May 2024)
All the Eco-Flow information can be found on our website: https://eco-flow.github.io.
We intend to develop novel, gold standard Nextflow pipelines for the agri-ecology field. These pipelines will fully adhere to the nf-core community guidelines, have complete unit testing with nf-test and use containerised environments published to our quay.io space: quay.io/user/ecoflowucl.
The intention if for all our pipelines to be deployable in any environment (local, on-prem HPC or cloud) utilising either Docker or Singularity for containerisation.
At Eco-Flow we want to help make deploying large-scale bioinformatics pipelines as easy for you as possible which is why everything we produce is public. This includes the configuration files for specific on-premise HPCs. If you want to see if we have already configured Nextflow for you HPC then check out Eco-Flow/configs.
- Eco-Flow/synteny - A pipeline that compares gene synteny between chromosome level genome assemblies.