Cell-Free DNA Ending-Position Analysis for Tissue Classification
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Solution Overview
Problem
The precise patterns of DNA fragmentation in cell-free plasma and serum samples are not well understood, limiting their practical applications, particularly in diagnostic settings.
Innovation Solution
Analyzing the fragmentation patterns of cell-free DNA by identifying preferred ending positions and using them to determine the proportional contribution and genotype of specific tissue types, such as fetal or tumor tissues, through methods involving sequencing and alignment to a reference genome.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If DNA fragmentation analysis is performed to determine tissue contribution proportions, then diagnostic accuracy is improved, but the complexity of the analysis method increases
Solution Approach 1:
The method segments the complex DNA fragmentation analysis into distinct computational steps: identifying preferred ending positions, calculating separation values between local maxima, and determining tissue contribution proportions. This segmentation transforms an otherwise intractable complex analysis into manageable, systematic processing steps that can be implemented through computer algorithms.
Solution Approach 2:
The method performs preliminary identification of preferred ending positions and local maxima in the fragmentation pattern before conducting the actual tissue contribution analysis. By pre-processing the DNA fragmentation data to identify these characteristic positions, the method simplifies subsequent calculations and improves diagnostic accuracy without requiring complex real-time analysis.
2Measurement precision
If preferred ending positions are identified through comparing local maxima to determine tissue contribution, then measurement precision is improved, but the difficulty of detecting and measuring increases
Solution Approach 1:
The method replaces complex manual or experimental detection methods with computational analysis of sequencing data. By using computer algorithms to identify local maxima and calculate separation values in the DNA fragmentation pattern, the method achieves high measurement precision while reducing the practical difficulty of detection compared to traditional experimental approaches.
3Loss of information
If fragmentation pattern analysis is used to determine genotype and proportional contribution, then information obtained is more comprehensive, but the loss of time in analysis increases
Solution Approach 1:
The method focuses on analyzing specific characteristic features (preferred ending positions and local maxima separation) rather than performing exhaustive analysis of the entire fragmentation pattern. This partial action approach extracts the most informative elements needed for genotype and tissue contribution determination, achieving comprehensive information gain with reduced analysis time compared to complete pattern analysis.
Data Source
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AI summary
A method of analyzing a biological sample, comprising: identifying at least one genomic region having a fragmentation pattern specific to a first tissue type; analyzing a plurality of cell-free DNA molecules from the biological sample, the biological sample including cell free DNA molecules from a plurality of tissues types that includes the first tissue type, wherein analyzing a cell-free DNA molecule includes: determining a genomic position in a reference genome corresponding to at least one end of the cell-free DNA molecule; identifying a first set of first genomic positions, each first genomic position having a local minimum of ends of cell-free DNA molecules corresponding to the first genomic position; identifying a second set of second genomic positions, each second genomic position having a local maximum of ends of cell-free DNA molecules corresponding to the second genomic position; determining a first number of cell-free DNA molecules ending on any one of the first genomic positions in any one of the at least one genomic region; determining a second number of cell-free DNA molecules ending on any one of the second genomic positions in any one of the at least one genomic region; computing a separation value using the first number and the second number; and determining a classification of a proportional contribution of the first tissue type by comparing the separation value to one or more calibration values determined from one or more calibration samples whose proportional contributions of the first tissue type are known.