Genome Sequence Analysis Parallel Processing
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Solution Overview
Problem
Current genome sequence analysis methods are computationally intensive and time-consuming, requiring significant resources to align and analyze large amounts of data, which hinders rapid analysis.
Innovation Solution
The method involves distributing aligned reads to multiple computing nodes based on genomic position, duplicating reads that overlap bin boundaries, and generating a merged file by writing data from local files in parallel, while using non-indexed independent compression blocks and redundant data entries for efficient data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional sequential genome sequence analysis methods are used, then data integrity is maintained, but analysis time becomes excessively long and computational resources are overwhelmed
Solution Approach 1:
The patent divides the genome sequence data into multiple data bins distributed across different computing nodes. Each computing node processes a specific data bin independently, enabling parallel processing of genome alignment and analysis tasks. This segmentation allows the system to handle large-scale genomic data efficiently by breaking down the monolithic processing task into smaller, concurrent sub-tasks.
Solution Approach 2:
The patent introduces a distributed computing dimension by deploying analysis across multiple computing nodes rather than relying on a single sequential processor. By organizing data bins across multiple nodes and implementing parallel processing architectures, the system transforms the computational approach from one-dimensional sequential processing to multi-dimensional parallel processing, significantly accelerating analysis speed.
2Productivity
If data is distributed across multiple computing nodes for parallel processing, then analysis speed increases, but data management complexity and communication overhead increase
Solution Approach 1:
The patent implements a merging strategy where data bins from multiple computing nodes are systematically combined and integrated. The system merges results from parallel processing across nodes while maintaining data coherence through coordinated data structures. This merging approach allows the system to leverage parallel processing power while managing complexity through structured integration of distributed data.
Solution Approach 2:
The patent introduces intermediary mechanisms including data bins that act as buffers between computing nodes and the central coordination system. These intermediaries facilitate efficient data exchange and reduce direct communication overhead between nodes by providing structured data containers that can be processed and transferred systematically, thereby managing distributed system complexity.
3Reliability
If reads overlapping bin boundaries are duplicated across multiple data bins, then processing completeness is ensured, but data redundancy increases
Solution Approach 1:
The patent applies partial duplication by copying reads that overlap bin boundaries to adjacent data bins. This excessive action ensures that reads spanning multiple genomic regions are captured in each relevant bin, guaranteeing processing completeness. The duplication is partial rather than complete, occurring only for boundary-crossing reads, which balances reliability requirements with data volume management.
4Quantity of substance
If compression blocks are used for data storage, then storage efficiency improves, but data access and processing speed may be reduced
Solution Approach 1:
The patent segments compressed data into independent compression blocks that can be processed individually. Each compression block is self-contained and can be decompressed and accessed independently, allowing the system to retrieve only the specific blocks needed for current analysis tasks. This segmentation enables efficient storage while maintaining fast access speeds by avoiding the need to decompress entire data sets.
Data Source
AI summary
A method for facilitating rapid genome sequence analysis includes accessing an output stream of an alignment process that includes aligned reads of a biological sequence that are aligned to a reference genome. The method also includes distributing the aligned reads to a plurality of computing nodes based on genomic position. Each of the plurality of computing nodes is assigned to a separate data bin of a plurality of data bins associated with genomic position. The method also includes, for at least one aligned read determined to overlap separate data bins of the plurality of data bins, duplicating the at least one aligned read and distributing the at least one aligned read to separate computing nodes of the plurality of computing nodes that are assigned to the separate data bins.