Internal Quantification Standard for NGS Data Normalization
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Solution Overview
Problem
Next-Generation Sequencing (NGS) technologies face challenges in clinical and diagnostic applications due to high intra-lab and inter-lab variation, limited ability to distinguish clinically relevant organisms from commensals, and lack of accurate absolute quantification methods, leading to variability in genetic variation analysis and pathogen detection.
Innovation Solution
A universal internal quantification standard is introduced that can be added to samples during preparation, allowing for simultaneous quantification of multiple targets and accounting for assay-specific and matrix-derived variances, enabling normalization of sequencing data and accurate determination of nucleic acid concentrations across all samples.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If NGS is used to detect both highly and minimally concentrated organisms, then the dynamic range is extended, but the ability to distinguish clinically relevant organisms from commensals is reduced
Solution Approach 1:
The patent introduces an internal quantification standard (IQS) as an intermediary substance that competes with target nucleic acids for sequencing reads. By adding a known quantity of IQS to each sample, the system can calculate the input quantity of target nucleic acids based on the ratio of target reads to IQS reads, enabling accurate quantification across a wide dynamic range while maintaining the ability to distinguish clinically relevant organisms from commensals.
2Productivity
If NGS library preparation and sequencing reaction preparation are performed, then sequencing data is generated, but intra-lab and inter-lab variation increases
Solution Approach 1:
The patent implements a feedback mechanism by including an internal quantification standard throughout the entire library preparation and sequencing process. The IQS serves as a control that allows calculation of process efficiency and normalization of sequencing data. By comparing the observed number of IQS reads to the expected number based on input quantity, the system can identify and correct for variations in library preparation and sequencing efficiency across different labs and runs.
Solution Approach 2:
The internal quantification standard enables the sequencing assay to self-correct for technical variations. Each sample contains its own IQS that undergoes the same preparation steps, allowing the system to automatically normalize data and compensate for lab-specific protocols and reagent batches without requiring external calibration.
3Measurement precision
If relative quantification is performed using serial dilutions, then the relationship between read numbers and target abundance is established, but absolute quantification capability is lost
Solution Approach 1:
The patent transforms the quantification approach by changing the parameter of reference. Instead of using relative references (serial dilutions of unknown samples), the system introduces an absolute reference (IQS with known input quantity). This parameter change enables the calculation of absolute input quantities of target nucleic acids using the formula: input quantity = (number of target reads / number of IQS reads) × input quantity of IQS, while maintaining the linear relationship observed in relative quantification.
Data Source
AI summary
Methods and kits for normalization and quantification of sequencing data.