Partial Sequence Data Alignment for Early Variant Reporting
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Solution Overview
Problem
Current Next-Generation Sequencing (NGS) technologies, such as whole genome sequencing, are time-consuming, often taking over 45 hours to complete, which delays the identification of genetic variants crucial for emergency medical decisions, necessitating a method to analyze sequences more rapidly and provide early reports.
Innovation Solution
A method that aligns partial sequence data as it is generated, identifies structural and point mutations, and generates reports before the completion of sequencing, utilizing processors to operate in parallel and determine the optimal data amount for early variant reporting, allowing for quicker treatment planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If whole genome sequencing is performed using NGS technology, then comprehensive genetic variant identification is achieved, but analysis time increases to over 45 hours
Solution Approach 1:
The system performs preliminary alignment and variant identification on partial sequence data as it is being generated, rather than waiting for complete sequencing. This allows early detection of structural variants and point mutations, enabling report generation before the full 45-hour sequencing process completes, thus resolving the contradiction between comprehensive analysis and time consumption
Solution Approach 2:
The sequencing analysis is divided into segments: first read processing, second read processing, and iterative refinement stages. The system can generate preliminary reports after processing the first read and update reports as the second read completes, allowing incremental delivery of results without requiring complete sequencing data
2Loss of time
If partial sequence data is used for early variant identification, then analysis time is reduced, but measurement precision may be compromised
Solution Approach 1:
The system implements feedback mechanisms where preliminary variant calls from partial data are refined and updated as additional sequence data becomes available. The iterative process allows the system to correct false positives and confirm true variants, maintaining high precision while enabling early report generation
Solution Approach 2:
The system performs variant identification with partial sequence data (partial action) rather than waiting for complete data, accepting that some variants may require further confirmation. This approach enables timely reporting while maintaining adequate precision for clinical decision-making
3Measurement precision
If sequential processing of sequence data is used, then processing accuracy is maintained, but productivity decreases
Solution Approach 1:
The system maintains continuous processing by aligning and analyzing sequence data as it is generated from the sequencer, without idle waiting periods. Multiple processors work continuously on different aspects of data processing (alignment, variant calling, report generation), maximizing productivity while maintaining accuracy through iterative refinement
Data Source
AI summary
A method for analyzing sequences performed by one or more processors is provided, including aligning first sequence data generated at a first time point based on reference sequence data, in which the first time point is a time point after reading of a first read of a pair of paired-end reads is completed and at which a second read of the pair of paired-end reads is partially read, identifying a structural variant from the aligned first sequence data, and before reading the second read is completed, generating a first report including information on the identified structural variant.