Non-invasive Genetic Variation Detection via GC Bias Correction

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Solution Overview

Problem

Current methods for non-invasive detection of genetic variations, such as chromosome aneuploidy, microdeletions, and microduplications, face challenges in accurately determining these conditions due to sequence read count errors and the complexity of genetic variations in cell-free nucleic acid samples.

Innovation Solution

A method involving the analysis of nucleic acid sequence reads from circulating cell-free DNA, where GC bias is determined and used to calculate genomic section levels, reducing sequence read count errors and enabling the detection of chromosome aneuploidies, microdeletions, and microduplications by fitting relations between sequence read counts and GC content.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If sequence read counts are used directly to detect genetic variations, then detection capability is provided, but sequence read count errors cause false positives and false negatives

Engineering Contradiction:

Improvedetection accuracyVSAvoidfalse positive and false negative rate

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

The patent introduces GC bias as an intermediary factor that mediates between sequence read counts and genetic variation detection. By modeling the relationship between GC content and read counts, the method accounts for systematic biases in the sequencing process, thereby reducing false positives and false negatives while maintaining detection capability

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent transforms the raw sequence read count data by incorporating GC content parameters and fitting statistical relations (such as linear or quadratic models). This parameter transformation adjusts the data to compensate for sequencing biases, improving both measurement precision and reliability simultaneously

Inventive Principle:

Principle #35Parameter changes

2Reliability

If GC bias correction is applied to reduce sequence read count errors, then false positives and false negatives are reduced, but additional computational steps are required

Engineering Contradiction:

Improvefalse positive and false negative rateVSAvoidcomputational process complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent performs GC bias assessment and model fitting as preliminary actions before final genetic variation detection. By pre-characterizing the GC bias patterns in the sequencing data and establishing correction models in advance, the method reduces errors efficiently without adding significant complexity to the main detection workflow

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent implements a feedback mechanism where the fitted relation between GC content and read counts is used to adjust and correct the sequence read count data. This feedback loop continuously refines the detection accuracy by comparing observed read counts with expected counts based on GC content, thereby reducing false positives and false negatives

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20220383977A1Methods and processes for non-invasive assessment of genetic variations

Publication Date: 2022.12.01 SEQUENOM INC

AI summary

Provided herein are methods, processes and apparatuses for non-invasive assessment of genetic variations.