NGS Pathogen Detection With Filtered Read Classification
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Solution Overview
Problem
Traditional DNA sequencing methods for diagnosing infectious diseases are limited by long processing times and high false-positive rates, requiring manual expert interpretation, which hinders timely and accurate clinical diagnosis.
Innovation Solution
A method and system using next-generation sequencing (NGS) that applies alignment algorithms like SNAP and RAPSearch, filters and classifies sequence reads, and provides rapid taxonomic classification to identify pathogens accurately, reducing false positives and enabling quick clinical interpretation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional DNA sequencing alignment methods are used to identify pathogens, then comprehensive sequence comparison can be performed, but processing time becomes excessively long due to the large amount of data to compare
Solution Approach 1:
The patent segments the reference genome database into smaller, organized units and processes sequence reads through multiple filtering stages (quality filtering, alignment filtering, taxonomic filtering) rather than comparing all sequences at once. This segmentation allows comprehensive analysis while reducing overall processing time by handling data in manageable chunks.
Solution Approach 2:
The patent performs preliminary filtering and classification of sequence reads before final pathogen identification. By pre-processing the data through multiple filtering stages and organizing reference genomes in advance, the system reduces the computational burden during the actual alignment process, thereby decreasing processing time while maintaining identification accuracy.
2Reliability
If comprehensive sequence alignment is performed against large reference databases, then pathogen detection sensitivity is improved, but false positive rates increase due to the vast amount of data
Solution Approach 1:
The patent introduces intermediary filtering steps between sequence alignment and final pathogen identification. These intermediaries include quality filters, alignment score thresholds, and taxonomic classification filters that mediate between raw alignment data and final results, thereby reducing false positives while preserving true pathogen detections.
Solution Approach 2:
The patent implements feedback mechanisms where alignment results are evaluated against multiple criteria (quality scores, taxonomic consistency, read coverage) and iteratively refined. Reads that fail filtering criteria are excluded or re-evaluated, creating a feedback loop that continuously improves result accuracy and reduces false positives while maintaining detection sensitivity.
3Measurement precision
If manual expert interpretation is used to analyze sequencing alignment results, then diagnostic accuracy is improved, but workflow efficiency and productivity decrease
Solution Approach 1:
The patent implements automated filtering, classification, and interpretation algorithms that perform tasks previously requiring manual expert analysis. The system self-evaluates alignment results through multiple filtering stages and automatically identifies pathogens based on predefined criteria, thereby maintaining diagnostic accuracy while eliminating the need for manual expert interpretation and significantly improving workflow efficiency.
Solution Approach 2:
The patent replaces the mechanical process of manual expert interpretation with automated computational algorithms. The filtering and classification system uses algorithmic rules and automated decision-making to interpret sequencing results, substituting human manual analysis with an automated system that maintains accuracy while dramatically increasing productivity and reducing turnaround time.
4Measurement precision
If multiple filtering and classification stages are applied to sequence reads, then false positives are reduced and accuracy is improved, but computational complexity and processing requirements increase
Solution Approach 1:
The patent segments the complex analysis pipeline into distinct, modular filtering and classification stages. Each stage handles a specific aspect of data processing (quality filtering, alignment filtering, taxonomic filtering), making the overall complex system manageable through segmentation into smaller, well-defined components that can be independently optimized and maintained.
Data Source
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AI summary
Embodiments are directed to systems and methods for pathogen detection using next-generation sequencing (NGS) analysis of a sample. Embodiments may apply alignment algorithms (e.g., SNAP and/or RAPSearch alignment algorithms) to align individual sequence reads from a sample in a next-generation sequencing (NGS) dataset against reference genome entries in a classified reference genome database. Embodiments of the present invention may include classifying, filtering, and displaying results to a clinician that can then quickly and easily obtain the results of the sequencing to identify a pathogen or other genetic material in a sample that is being tested. A negative sample and a corresponding database can be used to remove contaminants from a list of candidate pathogens. Thus, embodiments are directed to a system that is configured to filter the results of a sequencing alignment and classify a sample quickly.