Partitioned Nucleic Acid Sequencing for False-Positive Mutation Detection
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Solution Overview
Problem
Current methods for analyzing cell-free DNA in liquid biopsies face challenges due to the low concentration and heterogeneity of DNA, particularly in detecting epigenetic changes like DNA methylation, as hypermethylated DNA can contain damaged bases leading to false-positive mutations.
Innovation Solution
The method involves partitioning DNA into hypermethylated and hypomethylated partitions, tagging them with molecular barcodes, and applying more stringent criteria for calling C to T and G to A transition mutations in the hypermethylated partition to reduce false positives, using different thresholds and background error rates for each partition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If DNA from hypermethylated partitions is used for sequence analysis, then epigenetic changes can be detected, but false-positive mutations increase due to damaged bases
Solution Approach 1:
The patent segments the DNA sample into distinct hypermethylated and hypomethylated partitions based on methylation status. This segmentation allows separate analysis of each partition with appropriate criteria, preventing false-positive mutations from contaminating the overall sequence determination while preserving the ability to detect true epigenetic changes in the hypermethylated fraction.
Solution Approach 2:
The patent applies different stringency criteria for mutation calling in different regions (partitions) of the DNA data. Specifically, more stringent requirements are applied to hypermethylated partitions where deamination damage occurs, while standard criteria are used for hypomethylated partitions. This local differentiation of quality control measures resolves the contradiction by allowing sensitive detection in appropriate contexts while maintaining reliability where damage is problematic.
2Reliability
If stringent criteria are applied to call mutations in hypermethylated partitions, then false-positive mutations are reduced, but sensitivity for detecting actual mutations decreases
Solution Approach 1:
By segmenting the data into hypermethylated and hypomethylated partitions, the patent enables different stringency levels to be applied to each segment. The hypermethylated partition uses stringent criteria to filter false positives from deamination damage, while the hypomethylated partition uses standard criteria to maintain sensitivity. The combined results achieve both high specificity and sensitivity overall.
Solution Approach 2:
The patent changes the mutation calling parameters (stringency thresholds) based on the methylation status of the DNA partition. By adjusting these parameters dynamically according to the partition characteristics, the method optimizes both specificity (reducing false positives in hypermethylated regions) and sensitivity (maintaining detection capability in hypomethylated regions).
Data Source
AI summary
DNA damage (e.g., cytosine deamination) can appear more frequently in hypermethylated partitions of DNA (e.g., cell-free DNA) samples, than in hypomethylated partitions. Embodiments include sequencing hypermethylated partitions and hypomethylated partitions wherein calling a C to T or G to A transition mutation relative to a reference sequence based on sequences of molecules from the hypermethylated partition requires observation of the transition mutation in a greater number of molecules than calling a C to T or G to A transition mutation relative to the reference sequence based on sequences of molecules from the hypomethylated partition, or C to T or G to A transition mutations are not called relative to a reference sequence based on sequences of molecules of the hypermethylated partition.