Non-Invasive Genetic Variation Assessment Using Adaptive Genomic Binning
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Solution Overview
Problem
Current methods for non-invasive genetic variation assessment, particularly in prenatal diagnostics, face challenges in accurately identifying fetal genetic variations due to the heterogeneity of nucleic acid species in maternal blood samples, leading to inefficiencies in diagnosing conditions like aneuploidies and microdeletions.
Innovation Solution
The method involves partitioning genomic regions based on sequencing coverage variability and GC content, adjusting portion lengths, and using weighting factors to refine genomic regions, enabling precise estimation of fetal fraction and detection of genetic variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If genomic regions are partitioned into fixed portions, then the analysis process is simplified, but the accuracy of fetal fraction estimation deteriorates due to heterogeneous sequencing coverage and GC content variability
Solution Approach 1:
The patent divides the genome into multiple bins or segments, allowing different partitioning strategies to be applied to different regions. This segmentation enables the system to handle heterogeneous genomic regions (with varying GC content and sequencing coverage) separately, improving fetal fraction estimation accuracy while maintaining manageable analysis complexity through systematic processing of individual bins.
Solution Approach 2:
The patent implements region-specific partitioning where each genomic bin is analyzed with parameters tailored to its local characteristics (GC content, sequencing depth, mappability). This local quality approach allows the system to optimize fetal fraction estimation for each genomic region individually, rather than applying a uniform partitioning scheme that would compromise accuracy in heterogeneous regions.
2Ease of manufacture
If uniform portion lengths are used for all genomic regions, then the partitioning process is easier to implement, but the detection accuracy of genetic variations deteriorates due to ignoring GC content and coverage variability
Solution Approach 1:
The patent employs dynamic partitioning where bin sizes and boundaries are adjusted based on genomic region characteristics such as GC content, sequencing coverage, and mappability. This dynamic approach allows the partitioning scheme to adapt to local genomic variations, improving genetic variation detection accuracy while maintaining computational feasibility through algorithmic automation.
Solution Approach 2:
The patent changes partitioning parameters (bin size, boundaries, weighting factors) based on genomic region properties. By adjusting these parameters dynamically according to GC content and sequencing coverage variability, the system achieves accurate genetic variation detection without requiring manual optimization for each genomic region, thus maintaining ease of implementation.
3Device complexity
If all genomic regions are analyzed with equal weighting, then the analysis is more straightforward, but the reliability of fetal fraction estimation deteriorates due to heterogeneous nucleic acid species in different regions
Solution Approach 1:
The patent applies local quality by assigning region-specific weighting factors that account for differences in sequencing coverage, GC content, and mappability across genomic regions. This allows the system to give appropriate weight to each region's contribution to fetal fraction estimation, improving reliability while maintaining manageable analysis complexity through systematic weighting schemes.
Solution Approach 2:
The patent changes the weighting parameters for different genomic regions based on their characteristics. By adjusting these parameters dynamically, the system achieves reliable fetal fraction estimation that accounts for heterogeneous nucleic acid species without requiring complex manual analysis, thus balancing reliability with analysis simplicity.
Data Source
AI summary
Provided herein are methods, processes and apparatuses for non-invasive assessment of genetic variations that make use of nucleic acid fragments from circulating cell free nucleic acid. Also provided herein are methods for partitioning one or more genomic regions of a reference genome into a plurality of portions according to one or more features.