MegaBOLT
Accelerates bioinformatics analysis for genome and exome sequencing, enhancing speed and efficiency.
Overview
The MegaBOLT Bioinformatics Analysis Accelerator Series is a specialized system developed by MGI to enhance the speed of bioinformatics analysis, specifically designed for massively parallel sequencing (MPS). It significantly accelerates the analysis of Whole Genome Sequencing (WGS), Whole Exome Sequencing (WES), and Panel Sequencing for both germline and somatic data, achieving speeds up to 100 times faster than traditional algorithms.
MegaBOLT integrates with the ZMART bioinformatics application market, offering over 100 add-on applications to extend its functionality. It is characterized by its ultra-fast processing, high integration, user-friendly interface, and cost-effectiveness, which collectively contribute to reduced computing costs and time savings, facilitating efficient business development.
Key Features
- Supports accelerated algorithms such as SOAPnuke, Minimap2, BWA, GATK HaplotypeCaller, and MuTect2 through a multi-stream, highly parallelized computing architecture.
- Integrated multi-task scheduling system allows simultaneous multi-task computing on a single server, improving computing efficiency by 38% to 52%.
- Single-task mode enhances performance by 13% to 30% when analyzing individual tasks.
In terms of precision, MegaBOLT maintains high accuracy even after speed enhancements. It includes a deep learning variant calling module, MegaBOLT-DV, optimized through algorithmic and neural network model training. When used with PCR-Free library preparation and MGI DNBSEQ sequencing technologies, it achieves a variant calling precision of 99.9% for SNPs and 99% for INDELs. Additionally, the MegaBOLT-RC recalibrating module, based on machine learning, further enhances precision without requiring extensive computing resources.
Overall, MegaBOLT is an invaluable asset for laboratories, hospitals, research institutes, and enterprises seeking to expedite their genomic data analysis processes.

