This solution has been replaced by the AWS Solution for secondary analysis:

https://aws.amazon.com/solutions/implementations/genomics-secondary-analysis-using-aws-step-functions-and-aws-batch/

Genomics Research on AWS

This project demonstrates how to run a large-scale, genomics secondary-analysis pipeline on AWS using AWS Step Functions and AWS Batch. You can learn more about how we used the new AWS Step Functions integration with AWS Batch in our blog post, Building Simpler Genomics Workflows on AWS Step Functions.

PREREQUISITES

• AWS CLI
• Admin permissions for deployment

DEPLOY

Will build and deploy everything needed to run a secondary-analysis pipeline on AWS. This includes:

1. Custom AMI with 1TB scratch volume using the ECS AMI for your region (10 min)
2. Isaac, Strelka, Samtools-Stats and SnpEff as Docker images in ECR (40 min)
3. AWS Batch queues, compute environments, job definitions and an AWS Step Functions state machine (10 min)
4. Roles and buckets needed.

$ setup.sh 

USAGE

Run the Workflow

Copy the workflow input that was output to the terminal window after the deployment completed. Use that input to run the pipeline in the StepFunctions console. You can also find example workflow inputs in the outputs section of the batch-genomics-pipeline Cloudformation stack.

Update Pipeline Stack

Deploy changes made to local Cloudformation templates.

$ update.sh

Teardown Pipeline Stack

Deletes everything except the custom AMI and ECR images.

$ teardown.sh