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Genome-wide association studies identify genetic variations associated with a target disease or trait. Researchers and clinicians can use this information to better detect, treat and prevent chronic health conditions. This Solution Accelerator notebook builds on top of Glow

Home Page: https://www.databricks.com/solutions/accelerators/genome-wide-association-studies

License: Other

Python 100.00%

glow-solution-accelerator's Introduction

glow-solution-accelerator

About Glow

Glow is an open-source toolkit for working with genomic data at biobank-scale and beyond. The toolkit is natively built on Apache Spark, the leading unified engine for big data processing and machine learning, enabling the scale of the cloud for genomics workflows.

This accelerators demonstrates how to run sample glow workloads as a Multi-Task Job in Databricks on AWS and Azure.

To run this accelerator, clone this repo into a Databricks workspace. Attach the RUNME notebook to any cluster running a DBR 11.0 or later runtime, and execute the notebook via Run-All. A multi-step-job describing the accelerator pipeline will be created, and the link will be provided. Execute the multi-step-job to see how the pipeline runs.

The job configuration is written in the RUNME notebook in json format. The cost associated with running the accelerator is the user's responsibility.

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