Genomics workflows, Part 7: analyze public RNA sequencing data using AWS HealthOmics

This article discusses how life science organizations can use AWS HealthOmics and AWS Step Functions to automate and analyze public RNA sequencing data for clinical diagnostics. It allows researchers to quickly test hypotheses against larger datasets.

Specifically, the article covers:

• The use case of analyzing RNA sequencing (RNA-Seq) data from the Gene Expression Omnibus (GEO) repository using Nextflow workflows
• The solution architecture involving AWS HealthOmics for compute and workflow management, and AWS Step Functions for orchestrating data ingestion and analysis
• Implementation details for dataset ingestion using AWS Batch jobs, tracking status in DynamoDB, and generating sample sheets for HealthOmics analysis
• The HealthOmics RNA-Seq analysis workflow steps, including FASTQ file ingestion, monitoring status, and storing output BAM files
• Conclusion highlighting how HealthOmics simplifies gaining insights from omics data, combined with Step Functions for end-to-end automation