Sequencing Data Analysis Real-Time Haplotype Phasing
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Solution Overview
Problem
The rapid expansion of human genetics understanding, fueled by large-scale sequencing technologies, poses significant challenges in data production and bioinformatics, particularly in analyzing the vast volume of sequencing data and distinguishing between nearly identical sequencing reads from paternal or maternal origins.
Innovation Solution
A method and computer program product that enable real-time analysis of sequencing data by receiving and comparing sequencing reads with other sequences during ongoing sequencing assays, utilizing barcodes to identify and group sequencing reads, and employing algorithms for haplotype phasing, variant identification, and error distinction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If real-time analysis of sequencing data is performed, then analysis time is reduced and productivity is improved, but computational complexity and resource requirements increase
Solution Approach 1:
The patent performs alignment operations in advance during the sequencing process itself, rather than waiting for complete sequencing to finish. By pre-aligning reads as they become available and using predictive algorithms to anticipate future reads, the system reduces overall analysis time while managing computational resources efficiently
Solution Approach 2:
The analysis process is divided into multiple independent modules including real-time alignment, variant identification, haplotype phasing, and error correction. Each module processes specific aspects of the data independently, allowing parallel computation and reducing the computational burden on any single system component
2Measurement precision
If sequencing reads are compared with other sequences in real-time, then analysis accuracy is improved, but data volume processing requirements increase
Solution Approach 1:
The system extracts and processes only the most critical information from each sequencing read during real-time analysis, such as identifying variants, errors, and haplotype assignments. By focusing computation on high-value data elements rather than processing every base pair uniformly, the system maintains accuracy while reducing overall data processing requirements
Solution Approach 2:
The patent performs preliminary filtering and classification of sequencing reads during the sequencing process itself, identifying and separating high-quality reads from low-quality reads before final analysis. This pre-sorting reduces the volume of data that requires intensive processing while maintaining the accuracy of the final results
3Productivity
If automated pipelines are developed for data analysis, then workflow efficiency is improved, but algorithm development complexity increases
Solution Approach 1:
The patent develops a unified computational framework that performs multiple functions including alignment, variant identification, error correction, and haplotype phasing within a single integrated system. By designing a multi-functional platform rather than separate specialized tools, the system improves workflow efficiency while managing algorithmic complexity through modular architecture
Solution Approach 2:
The automated pipeline incorporates continuous feedback mechanisms where analysis results are fed back into the sequencing process to adjust real-time alignment parameters and improve future read processing. This iterative feedback loop enhances workflow efficiency while the systematic approach to algorithm optimization manages computational complexity
Data Source
AI summary
The invention described herein solves challenges in providing a proficient, rapid and meaningful analysis of sequencing data. Methods and computer program products of the invention allow for a system to receive, analyze, and display sequencing data in real-time. The invention provides solutions to several difficulties encountered in assembling short sequencing-reads, and by doing so the invention improves the worth and significance of sequencing data.