Integrated Circuit Genomic Pipeline With Parallel Processing Engines
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Solution Overview
Problem
Current bioinformatics methods for analyzing genomic data are labor-intensive, time-consuming, and prone to errors, particularly in assembling full-length genomic sequences and determining variants, which hinders the efficient processing and analysis of the vast amounts of data generated in genomic sequencing.
Innovation Solution
Implementing bioinformatics protocols on an integrated circuit processing platform using hardware accelerators with hardwired digital logic circuits, configured as processing engines, to perform tasks such as sequence analysis, mapping, alignment, and sorting, optimizing these processes for faster and more accurate execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional software-based bioinformatics methods are used for genomic data analysis, then flexibility and ease of implementation are maintained, but processing speed and productivity are insufficient
Solution Approach 1:
The patent replaces software-based processing with hardware-based processing using FPGAs and ASICs. The bioinformatics algorithms are implemented as hardwired digital logic circuits that perform sequence analysis, mapping, alignment, and sorting operations in parallel, achieving speeds thousands of times faster than traditional software implementations while maintaining the same analytical functions.
Solution Approach 2:
The patent divides the genomic data processing task into multiple parallel processing engines, each handling specific operations such as k-mer extraction, hash table lookup, sequence alignment, and variant calling. This segmentation enables simultaneous execution of multiple processing steps, dramatically increasing overall productivity without requiring a single complex processor.
2Loss of time
If manual or software-based assembly of full-length genomic sequences is performed, then accuracy can be maintained through careful analysis, but the process becomes labor-intensive and time-consuming
Solution Approach 1:
The hardware processing system performs automated assembly of full-length genomic sequences through dedicated circuits that automatically execute assembly algorithms. The system self-manages the complex task of reconstructing genomes from short reads using parallel processing, eliminating the need for manual intervention while maintaining high accuracy through error correction circuits.
Solution Approach 2:
The patent implements preliminary processing steps in hardware, including k-mer extraction, hash table generation, and quality filtering, before the main assembly process. These preliminary actions prepare the data in advance for rapid assembly, reducing the overall time required for complete genomic analysis while maintaining accuracy through pre-validated processing steps.
3Productivity
If hardware accelerators are implemented to speed up processing, then productivity and speed improve, but device complexity and manufacturing difficulty increase
Solution Approach 1:
The patent designs universal hardware processing engines that can perform multiple bioinformatics operations through configurable logic units. The same hardware architecture can be programmed to execute different algorithms for sequence alignment, variant calling, or genome assembly, reducing manufacturing complexity by using standardized modules rather than custom circuits for each function.
Solution Approach 2:
The patent implements dynamically reconfigurable logic circuits using FPGAs that can change their functionality based on the processing task at hand. This dynamic capability allows a single hardware device to adapt to different genomic analysis requirements without requiring physical reconfiguration or multiple specialized devices, simplifying manufacturing while maintaining high productivity.
4Speed
If parallel processing is used to reduce analysis time, then speed improves, but the complexity of coordinating and managing processing tasks increases
Solution Approach 1:
The patent merges the control functions for multiple parallel processing engines into a single integrated control unit within the hardware architecture. This unified controller coordinates data flow, manages memory access, and synchronizes processing steps across all engines, reducing the complexity that would otherwise arise from managing multiple independent control systems.
Data Source
AI summary
A system, method and apparatus for executing a sequence analysis pipeline on genetic sequence data includes a structured ASIC formed of a set of hardwired digital logic circuits that are interconnected by physical electrical interconnects. One of the physical electrical interconnects forms an input to the structured ASIC connected with an electronic data source for receiving reads of genomic data. The hardwired digital logic circuits are arranged as a set of processing engines, each processing engine being formed of a subset of the hardwired digital logic circuits to perform one or more steps in the sequence analysis pipeline on the reads of genomic data. Each subset of the hardwired digital logic circuits is formed in a wired configuration to perform the one or more steps in the sequence analysis pipeline.