cfDNA Variant Calling Using gDNA Fragment Length Separation
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Solution Overview
Problem
Conventional systems struggle to differentiate between germline and somatic mutations in cell-free DNA due to noise and biases, relying on human expertise, and fail to accurately classify genetic variants when allelic fractions are fuzzy.
Innovation Solution
A method involving the use of genomic DNA (gDNA) with longer fragment lengths than cell-free DNA (cfDNA) to distinguish somatic and germline variants by sequencing techniques, including targeted sequencing and differential tagging of gDNA and cfDNA, allowing for accurate classification based on allelic frequency comparisons.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If conventional systems use human expertise to differentiate germline and somatic mutations, then the ability to handle fuzzy allelic fractions is maintained, but automation and productivity are reduced
Solution Approach 1:
The patent introduces an intermediary computational model that mediates between raw sequencing data and variant classification. This model uses probabilistic frameworks to integrate multiple data sources (allelic fraction, fragment length, sequencing depth) and produce automated classifications, eliminating the need for human expert intervention while maintaining high accuracy through systematic integration of evidence
Solution Approach 2:
The system implements feedback mechanisms where computational models continuously refine their classifications by comparing predictions against known germline variants and adjusting probability scores. This iterative feedback process allows the automated system to learn from patterns in the data and improve its differentiation accuracy over time, matching the adaptive judgment of human experts
2Measurement precision
If noise and biases are present in sequencing data, then measurement precision deteriorates, but the system must still accurately classify variants with fuzzy allelic fractions
Solution Approach 1:
The patent transforms the measurement problem by changing from direct allelic fraction measurement to probabilistic parameter estimation. Instead of relying on crisp allelic fraction values that are degraded by noise, the system estimates probability distributions over possible genotypes, using Bayesian inference to incorporate prior knowledge and resolve ambiguities introduced by sequencing noise and biases
Solution Approach 2:
The system creates a composite assessment framework that integrates multiple measurement dimensions (allelic fraction, fragment length distribution, sequencing depth, quality scores) into a unified probabilistic classification. This composite approach allows the system to compensate for noise in individual measurements by synthesizing evidence across multiple parameters, thereby maintaining high reliability despite measurement imprecision
3Measurement precision
If gDNA is added to the assay mixture, then the ability to distinguish germline variants is improved, but device complexity and manufacturing complexity increase
Solution Approach 1:
The patent segments the DNA processing workflow into distinct functional stages: (1) selective lysis of nucleated cells to release cfDNA, (2) differential fragmentation to create size distributions characteristic of each DNA source, (3) selective amplification using primers that preferentially amplify cfDNA, and (4) sequencing. This segmentation allows gDNA to be added only at specific stages where it provides benefit, while minimizing its impact on overall process complexity through modular design
Data Source
AI summary
The present disclosure provides systems and methods to detect somatic or germline variants by providing a predetermined genomic DNA (gDNA) to an assay mixture, and capturing a sample of a subject's genetic information using a DNA sequencer and detecting genetic variants from the genetic information. A mutation may then be classified as being from a germline source if gDNA derived molecules have lengths inconsistent with those expected from cell-free DNA (cfDNA) derived molecules.