Short-Read Alignment and Sorting via Tiered BWT Memory
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Solution Overview
Problem
Conventional gene sequencing systems face challenges in performance and storage resource utilization, particularly in the seeding sub-stage of the SR Alignment sub-system, due to inefficient memory access patterns in the Burrows Wheeler Transform (BWT) algorithm, which leads to prolonged processing times and high storage requirements.
Innovation Solution
Implementing a hardware device that stores frequently accessed occurrence table entries in a faster memory type, reducing the need for random and sequential memory accesses during the seeding sub-stage by utilizing a combination of fast and slower memory types based on the available memory capacity and the number of short reads to be processed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the BWT algorithm is used for gene sequencing alignment, then the alignment can be performed, but the memory access time is prolonged due to random and sequential access patterns
Solution Approach 1:
The patent pre-calculates and stores occurrence tables during an offline phase, transforming the reference genome data into a format that enables faster online querying. This preliminary preparation eliminates the need for complex random access operations during actual gene sequencing alignment, significantly reducing processing time.
Solution Approach 2:
The patent divides the occurrence table into multiple segments or levels, allowing the system to process queries in a structured manner. This segmentation transforms the problematic random access pattern into a series of more predictable access patterns, improving memory access efficiency while maintaining alignment accuracy.
2Productivity
If conventional memory access patterns are used in the seeding sub-stage, then the alignment process can be completed, but the runtime is prolonged
Solution Approach 1:
The patent implements a dynamic memory access strategy that adapts to the specific characteristics of the occurrence table and query patterns. By dynamically adjusting access patterns based on the data structure and query requirements, the system optimizes runtime performance while maintaining processing efficiency.
Solution Approach 2:
The patent changes key parameters of the memory access process, including access patterns, data organization, and table structure. These parameter changes transform the inefficient conventional access patterns into optimized patterns that significantly reduce runtime while preserving the alignment functionality.
3Speed
If the occurrence table is stored in standard memory, then the system can function, but the memory access speed is insufficient for efficient processing
Solution Approach 1:
The patent introduces an intermediary data structure (the pre-processed occurrence table) that mediates between the reference genome and the alignment process. This intermediary transforms complex random access requirements into simpler, faster access patterns, improving memory access speed while managing system complexity through structured data organization.
Data Source
AI summary
In accordance with embodiments, a processing unit performs alignment of a short read (SR) against a reference sequence. The reference sequence comprises a first sequence of base pairs (bps). The SR comprises a second sequence of bps. The processing unit determines whether the SR is aligned. If the SR is not aligned, the processing unit receives the next SR and processes the next SR by repeating. If the SR is aligned, in response to the determination that the SR is aligned with the reference sequence at a first position in the reference sequence, the processing unit generates an SR metadata entry corresponding to the SR. The processing unit inserts the SR metadata entry to a linked list in a SR metadata collection. The position of the linked list in the SR metadata collection corresponds to the first position of the reference sequence where the SR is aligned.