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SeqsLab Jobs
Scaling multi-omics workflows from samples to results
From bioinformatics design and workflow management to workload acceleration and performance optimization, clinical laboratories and biotech enterprises demand an automated process of implicitly and dynamically scaling workflows as large-scale utilization increases. It all starts with a standardized workflow management infrastructure.
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SeqsLab Jobs builds on a cloud-native infrastructure and Cromwell workflow management system originally developed by the Broad Institute, and implements the GA4GH Workflow Execution Service and Tool Registry Service standards for workflow process orchestration. It empowers the biomedical industry to innovate and deliver analysis products at scale and speed.
Design automated workflows
Writing your own scientific, analytics, and machine learning workflows with OpenWDL, a human-readable and –writable description language. WDL in SeqsLab simplifies the development life cycle of data processing workflows from building and validation to production.
Accelerate a variety of workloads the common way
Connect to a variety of bioinformatics and SQL tools and run all data parallel operations directly from the SeqsLab lakehouse architecture. SeqsLab combines the best of structured data processing and data lake, but with richer optimization, higher performance, lower costs, and better support for ML workloads.
No cluster computing management required
Spinning up and down on-demand, independent Apache Spark serverless clusters allows for cost-performance efficiency. SeqsLab automates the workflow task scheduling and runs Apache Spark data processing jobs in parallel. It can execute heterogenous big data pipelines, save costs, and reduce turnaround times.
Ensure data, code, and execution integrity
Comply with regulatory requirements and ensure run-to-run reproducibility, consistency, and validity. The SeqsLab platform follows the IEC 62304 medical device software life cycle processes to audit and validate the integrity, accuracy, and versioning of data, analysis tools, and execution environments for the entire life cycle of workflows.
