CNV Detection via Genomic Bin Segmentation
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Solution Overview
Problem
Current methods for classifying copy number variations in sub-chromosome regions are limited in accuracy and sensitivity, particularly for detecting microdeletions and microduplications that are too small to be detected by conventional cytogenetic methods, and often require invasive procedures.
Innovation Solution
The use of a segmentation process and sequence read quantification methods to identify and classify copy number variations in sub-chromosome regions, employing genome-wide and focused sequence analysis to improve detection accuracy and sensitivity, and utilizing a system with processors and memory to execute instructions for classifying copy number variations based on changes relative to a reference set of samples.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional cytogenetic methods are used, then the testing procedure is simple, but the detection sensitivity and accuracy for microdeletions and microduplications are insufficient
Solution Approach 1:
The patent segments the chromosome into multiple genomic bins and analyzes read depth in each bin to detect copy number variations. This segmentation approach enables detection of microdeletions and microduplications that are too small to be detected by conventional cytogenetic methods, thereby improving measurement precision without requiring complex invasive procedures
Solution Approach 2:
The patent replaces mechanical cytogenetic methods (karyotyping, FISH) with molecular biology-based next-generation sequencing technology. This substitution enables detection of smaller genetic variations with higher accuracy while maintaining a relatively simple non-invasive testing procedure using only maternal blood samples
2Measurement precision
If invasive procedures are used to improve detection accuracy, then diagnostic precision improves, but patient safety and ease of operation deteriorate
Solution Approach 1:
The patent uses cell-free fetal DNA in maternal bloodstream as an intermediary to obtain fetal genetic information without direct fetal sampling. This intermediary approach allows non-invasive extraction of fetal DNA through maternal blood draw, maintaining diagnostic precision for copy number variations while eliminating the invasiveness and safety risks associated with amniocentesis or chorionic villus sampling
Solution Approach 2:
The patent analyzes copies of genomic sequences through next-generation sequencing of cell-free DNA. By sequencing multiple copies of genomic regions and analyzing read depth variations, the method achieves high diagnostic precision for detecting copy number variations while using a simple non-invasive blood draw procedure
3Reliability
If genome-wide analysis is performed to improve detection coverage, then the detection sensitivity increases, but the computational complexity and time required increase
Solution Approach 1:
The patent divides the genome into discrete bins and processes read depth data for each bin independently. This segmentation enables efficient parallel computation and reduces the time required for genome-wide analysis while maintaining high detection sensitivity through comprehensive coverage of all genomic regions
Solution Approach 2:
The patent performs preliminary processing of sequencing data including quality control, alignment to reference genome, and normalization before CNV detection. This preliminary action prepares the data in advance, reducing computational complexity and analysis time for the actual copy number variation detection while maintaining detection sensitivity
Data Source
AI summary
Technology provided herein relates in part to non-invasive classification of one or more genetic copy number variations (CNVs) for a test sample. Technology provided herein is useful for classifying a genetic CNV for a sample as part of non-invasive pre-natal (NIPT) testing and oncology testing, for example.