Back

Maloja: simple and scalable Snakemake workflow orchestration in the cloud

Giustizia, J.; Hodgson, W.; Andress, C.; Bilkhu, S.; Macklin, J.; Kess, T.

2024-07-02 bioinformatics
10.1101/2024.06.28.601236 bioRxiv
Show abstract

As sequencing technologies have matured, bioinformatics tasks have become more complex, computationally demanding, and data intensive. Workflow management software has been developed to aid in simplifying the replicable chaining of complex bioinformatics jobs, and cloud computing has emerged as a potential solution to the computational demands of this work. However, the capacity to effectively deploy these resources is limited by the expertise required to implement these solutions. Here, we develop Maloja, an easily deployed cloud workflow orchestrator. This tool interprets existing scientific workflows written in Snakemake and deploys them in appropriately scaled AWS cloud resources. We test the utility of this new toolset using previously published and custom built Snakemake workflows for ecological genomics tasks, revealing how this tool can facilitate the use of cloud resources without prior cloud architecture expertise.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.