Non-Invasive Genetic Variation Detection via Normalized Read Segmentation
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Solution Overview
Problem
Current methods for non-invasive genetic variation analysis, particularly for detecting chromosome aneuploidy, microduplication, or microdeletion, are limited in accuracy and efficiency, especially in identifying fetal or cancer-related genetic variations from circulating cell-free nucleic acid samples.
Innovation Solution
A computer-implemented method involving nucleotide sequence read normalization, wavelet and circular binary segmentation, and candidate segment identification to determine the presence or absence of genetic variations, utilizing paired-end nucleotide sequencing of blood, serum, or urine samples.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current methods are used for non-invasive genetic variation analysis, then the process is simpler, but the accuracy and reliability of detecting chromosome aneuploidy, microduplication, or microdeletion is limited
Solution Approach 1:
The method segments the normalized read count data into discrete segments using wavelet segmentation and circular binary segmentation algorithms. This segmentation allows for precise identification of candidate regions containing genetic variations by dividing the genome into manageable segments and analyzing each independently, thereby improving detection accuracy without overwhelming complexity
Solution Approach 2:
The method performs preliminary normalization of nucleotide sequence read counts mapped to genome portions before segmentation and analysis. This preliminary action of normalizing the data ensures that subsequent detection steps work with standardized, comparable values, improving the reliability of genetic variation detection while maintaining a systematic workflow
2Reliability
If traditional analysis methods are used, then the computational process is faster, but the ability to identify fetal or cancer-related genetic variations from circulating cell-free nucleic acid is insufficient
Solution Approach 1:
By segmenting the genome into discrete portions and analyzing each segment independently through wavelet and circular binary segmentation, the method reliably identifies genetic variations even in complex circulating cell-free nucleic acid samples. This segmented approach maintains computational efficiency while improving detection reliability for fetal or cancer-related variations
Solution Approach 2:
The method focuses computational resources on analyzing specific candidate segments identified through segmentation rather than processing the entire genome uniformly. This partial action approach concentrates analytical power where genetic variations are most likely to be detected, improving reliability without excessive time loss
Data Source
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AI summary
The present invention relates to a method for determining the presence or absence of a chromosome aneuploidy, microduplication, e.g. CNV, or microdeletion in a fetus or in a subject, optionally suffering from cancer, comprising: (a) normalizing counts of nucleotide sequence reads mapped to portions of a reference genome, which sequence reads are 1) reads of circulating cell-free nucleic acid from a test sample from a pregnant female bearing a fetus and 2) reads from nucleic acid fragments having lengths less than or equal to a selected fragment length, thereby providing normalized counts; and (b) determining the presence or absence of a chromosome aneuploidy, microduplication or microdeletion according to the normalized counts.