Dynamic Variant Thresholding in Liquid Biassay
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Solution Overview
Problem
Conventional liquid biopsy assays face challenges in accurately detecting somatic tumor mutations in cell-free DNA, particularly when tumor fractions are low, due to high variability in signal-to-noise ratios and difficulties in determining tumor fraction, leading to false negatives and incomplete genomic analysis.
Innovation Solution
The use of a dynamic variant filtering methodology based on Bayes' Theorem to adjust variant count thresholds locus-specifically, accounting for variant prevalence, sequencing errors, and allele fractions, improves the accuracy of somatic variant identification in liquid biopsy samples by tuning specificity and sensitivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional liquid biopsy assays use fixed variant count thresholds for detecting somatic mutations, then the assay protocol is simple and easy to implement, but the detection accuracy deteriorates due to high variability in signal-to-noise ratios and inability to account for locus-specific characteristics
Solution Approach 1:
The patent implements dynamic variant count thresholds that adjust based on locus-specific characteristics, tumor fraction estimates, and sequencing depth. Instead of using fixed thresholds, the system calculates adaptive thresholds for each genomic locus considering local error rates, variant prevalence, and sample-specific factors. This dynamic approach resolves the contradiction by making the filtering methodology responsive to varying signal-to-noise ratios across different genomic regions and samples.
Solution Approach 2:
The patent applies different filtering criteria and variant count thresholds for different genomic loci based on their specific characteristics. Each locus receives a customized threshold calculation that accounts for local sequencing error rates, mappability, and expected variant frequencies. This local quality approach improves measurement precision without requiring uniformly complex processing across the entire genome.
2Reliability
If liquid biopsy assays lower the variant count threshold to detect rare mutations in low tumor fraction samples, then sensitivity improves for early-stage cancer detection, but false positives increase due to sequencing errors and artifacts
Solution Approach 1:
The patent dynamically adjusts multiple parameters including variant count thresholds, tumor fraction estimates, and sequencing depth requirements based on sample characteristics and locus properties. By changing these parameters adaptively rather than using fixed values, the system maintains high sensitivity for detecting rare mutations while adjusting the false positive rate through locus-specific error modeling and quality filters.
Solution Approach 2:
The system incorporates feedback loops where tumor fraction estimates, sequencing quality metrics, and initial variant calls inform subsequent filtering decisions. The variant count thresholds are recalculated based on feedback from observed sequencing errors, mappability metrics, and comparison with reference genomes, allowing the system to distinguish true low-frequency variants from artifacts.
3Loss of information
If liquid biopsy assays use comprehensive genomic analysis to identify all potential mutations, then the completeness of genomic analysis improves, but the computational complexity and time required for analysis increases
Solution Approach 1:
The patent divides the genomic analysis into manageable segments or loci, processing each region independently with localized filtering parameters. This segmentation allows comprehensive coverage of the genome while enabling parallel processing and reducing the computational burden compared to analyzing the entire genome as a single unit. Each segmented region can be filtered and evaluated separately, improving overall analysis efficiency.
Data Source
AI summary
Methods, systems, and software are provided for validating a somatic sequence variant in a subject having a cancer condition. Sequence reads are obtained from sequencing cell-free DNA fragments in a liquid biopsy sample of the subject. Sequence reads are aligned to a reference sequence. A variant allele fragment count and locus fragment count are identified for a candidate variant that maps to a locus in the reference sequence. The variant allele fragment count is compared against a dynamic variant count threshold for the locus. The threshold is based on a pre-test odds of a positive variant call for the locus, based on the prevalence of variants in a genomic region including the locus in a cohort of subjects having the cancer condition. The somatic sequence variant in the subject is validated, or rejected, when the variant allele fragment count for the candidate variant satisfies, or does not satisfy, the threshold.