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Related Experiment Videos

Trellis for efficient data and task management in the VA Million Veteran Program.

Paul Billing Ross1,2, Jina Song1,2, Philip S Tsao3,4

  • 1Stanford Center for Genomics and Personalized Medicine, Stanford University, Stanford, CA, USA.

Scientific Reports
|December 2, 2021
PubMed
Summary
This summary is machine-generated.

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Trellis automates biomedical data processing from start to finish. This cloud framework efficiently manages large-scale genomic data, enabling faster analysis for projects like the VA Million Veteran Program.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Biomedical studies generate vast datasets, posing significant data processing challenges.
  • Efficient management and analysis of large-scale biomedical data are crucial for scientific advancement.

Purpose of the Study:

  • To introduce Trellis, a novel cloud-based framework for automated data and task management in biomedical research.
  • To address the challenges of data ingestion, processing, lineage tracking, and result presentation in large-scale studies.

Main Methods:

  • Developed Trellis, a cloud-based framework utilizing a graph database for workflow coordination.
  • Implemented a scalable microservice architecture for performing bioinformatics tasks.
  • Automated the end-to-end process from data ingestion to result presentation.

Related Experiment Videos

Main Results:

  • Trellis successfully automated the complete data processing pipeline.
  • The framework demonstrated fault-tolerance and scalability.
  • Enabled efficient variant calling on 100,000 human genomes from the VA Million Veteran Program.

Conclusions:

  • Trellis provides a robust and scalable solution for managing and processing large-scale biomedical data.
  • The framework facilitates efficient genomic analysis, exemplified by its application in a major veteran health initiative.
  • Automated data management frameworks are essential for accelerating discovery in modern biomedical research.