Trellis data management framework for biomedical research

Biomedical studies have become larger in size and yielded large quantities of data, yet efficient data processing remains a challenge. Trellis is a cloud-based data and task management framework that completely automates the process from data ingestion to result presentation, while tracking data lineage, facilitating information query, and supporting fault-tolerance and scalability. Using a graph database to coordinate the state of the data processing workflows and a scalable microservice architecture to perform bioinformatics tasks, Trellis has enabled efficient variant calling on 100,000 human genomes collected in the VA Million Veteran Program.

GitHub: https://github.com/StanfordBioinformatics/trellis-mvp-functions. Publication: https://www.nature.com/articles/s41598-021-02569-5.

Contents:

• Data model
  • Relationship patterns
  • Graph schema
• Application architecture
  • Creating nodes from data objects
  • Activating database triggers
  • Running database trigger queries
  • Creating job nodes
• Deployment
• Security
• Version 1.3 Update (In-dev)
  • Using a node label taxonomy
  • Using standard message classes
  • Switching to the Neo4j database driver
  • Simplifying database triggers
  • Using parameterized queries
• Trellis v1.3 Update Design Doc
  • Functions
  • Trellisdata Python Package
  • Database
• Node label ontology
  • Deployment configuration

Indices and tables

• Search Page