SQream Dramatically Accelerates HAIL Workflows in Genomics Research

By Raz Kaplan

6.26.2024 twitter linkedin facebook

The genomics field is experiencing a data deluge. With the human genome alone containing over three billion base pairs, just a single individual’s genetic data can easily translate into hundreds of millions of rows – often exceeding 500 million. Analyzing these massive datasets is crucial for unlocking new possibilities in personalized medicine, drug discovery, and more. However, analyzing these datasets can be computationally intensive, often bottlenecked by data preparation. Traditional frameworks like HAIL, while powerful for analysis, can struggle with the initial steps of loading and prepping vast amounts of genomic data. This is where SQream steps in, and recent research has shown significant performance improvements using SQream’s GPU-accelerated SQL platform.

HAIL’s Bottleneck: Slow Data Prep Hinders Research

HAIL, a popular framework for genome analysis, offers powerful tools for researchers. However, its reliance on traditional CPU processing can be a roadblock when dealing with massive datasets. Data preparation, a critical initial step involving loading, cleaning, and transforming data, becomes a time bottleneck in HAIL, slowing down research progress.

SQream to the Rescue: Real-World Performance Gains

 

Use case 3 (incrementally increasing sample sizes) – Data loading, preprocessing and reloading with SQream took about 2 minutes for each increment, as opposed to a progression of 10 to 14 minutes with HAIL as sample size increased:


Recent research explored how SQream tackles this data prep hurdle and accelerates HAIL workflows with its powerful GPU-accelerated SQL engine:

  • Up to 90% faster preprocessing: SQream significantly reduced data loading and preprocessing times. In one study, preprocessing data for 100 individuals – typically a 70-hour process with HAIL – was completed in just 6 hours and 25 minutes with SQream, demonstrating a near 90% improvement.
  • Scalable performance for growing datasets: As the number of samples increased, SQream maintained its speed. Adding new data points didn’t significantly slow down processing, allowing researchers to seamlessly scale their studies without sacrificing performance.
  • Faster time-to-insights: By accelerating data preparation and the overall workflow, SQream enabled researchers to obtain results much faster. This translates to quicker decision-making and faster progress in research endeavors.

The Impact: Faster Breakthroughs in Genomics

 

 

These findings demonstrate the significant impact SQream can have on HAIL workflows. By dramatically reducing data preparation times and enabling researchers to handle larger datasets efficiently, SQream empowers researchers to unlock the full potential of HAIL. This translates to faster breakthroughs and advancements in genomics research.

Ready to See the Results for Yourself?

Contact SQream to read the full research report and see how SQream’s GPU-accelerated SQL platform can accelerate your HAIL workflows. Get a demo to experience the power of SQream firsthand.