Integrated Circuit Genomic Pipeline for Fast Sequence Analysis
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Solution Overview
Problem
Current bioinformatics systems face challenges in efficiently processing large volumes of genomic data from Next Gen Sequencers, requiring significant computational resources and incurring high costs, while existing software-based methods are labor-intensive and prone to errors.
Innovation Solution
A hardware-accelerated platform using integrated circuits, such as FPGAs or ASICs, with pre-configured hardwired digital logic circuits to perform bioinformatics protocols like mapping, alignment, sorting, and variant calling, optimizing processing speed and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If software-based methods are used for genomic data processing, then flexibility and ease of implementation are improved, but processing speed and computational efficiency deteriorate
Solution Approach 1:
The patent replaces software-based processing (mechanical system) with hardware-based processing using FPGAs and ASICs. The bioinformatics algorithms are implemented as hardwired digital logic circuits that perform mapping, alignment, sorting, and variant calling operations in parallel, achieving orders-of-magnitude speedup while maintaining the functional capabilities of the original software system
Solution Approach 2:
The patent creates hardware copies of the bioinformatics processing logic by implementing algorithms as configurable logic blocks in FPGAs and fixed logic in ASICs. Multiple identical processing units are instantiated to handle multiple genomic data streams simultaneously, enabling parallel processing that maintains software flexibility while achieving hardware-speed performance
2Device complexity
If traditional computing platforms are used, then system complexity is reduced, but processing power and accuracy deteriorate
Solution Approach 1:
The patent segments the genomic data processing pipeline into distinct functional modules (mapping, alignment, sorting, variant calling) that can be independently implemented and optimized in hardware. Each module is implemented as separate configurable logic blocks that can be configured to handle specific algorithmic requirements, improving both accuracy and maintainability
Solution Approach 2:
The patent transitions from sequential software processing to parallel hardware processing by adding the dimension of spatial concurrency. Multiple processing units operate simultaneously on different data streams, and the FPGA fabric provides multiple interconnection paths for data flow, enabling massive parallelism that improves processing power without proportionally increasing system complexity
3Productivity
If hardware-accelerated platforms are used, then processing speed and accuracy are improved, but device complexity and development difficulty increase
Solution Approach 1:
The patent implements universal bioinformatics processing platforms using FPGAs that can be reconfigured to perform multiple different algorithms and processing tasks. The same hardware platform can be programmed to execute different mapping algorithms, alignment methods, or variant calling approaches, reducing the need for multiple specialized hardware devices while maintaining high processing speeds
Solution Approach 2:
The patent introduces high-speed memory interfaces and data buffers as intermediary components between the hardware processing logic and external data sources. These intermediaries manage data flow efficiently, reducing the complexity of direct hardware-to-storage connections while enabling sustained high processing speeds by decoupling data access from computation
4Productivity
If more computational resources are allocated, then processing capacity increases, but cost and power consumption increase
Solution Approach 1:
The patent changes the fundamental parameter of processing architecture from general-purpose software execution to specialized hardware implementation. By implementing bioinformatics algorithms as fixed or configurable logic circuits, the system achieves higher processing capacity per watt because hardware logic performs operations directly in circuitry rather than through software interpretation, dramatically improving energy efficiency
Data Source
AI summary
A system, method and apparatus for executing a bioinformatics analysis on genetic sequence data includes an integrated circuit 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 integrated circuit that may be connected with an electronic data source for receiving reads of genomic data. The hardwired digital logic circuits may be 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 bioinformatics analysis on the reads of genomic data. Each subset of the hardwired digital logic circuits may be formed in a wired configuration to perform the one or more steps in the bioinformatics analysis.