SNP Panel Selection for Genetic Sample Identification
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Solution Overview
Problem
Current genetic analysis methods for identifying and distinguishing biological samples, such as cell lines and tumor samples, are time-consuming and complex due to the need to analyze hundreds or thousands of single nucleotide polymorphisms (SNPs), making them costly and inefficient.
Innovation Solution
The methods involve selecting a manageable set of SNPs through statistical analysis to create a genetic barcode for each sample, allowing for accurate identification and discrimination using a smaller, more cost-effective panel of SNPs tailored to the specific samples being analyzed, rather than relying on larger, randomly selected sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If hundreds or thousands of SNPs are analyzed in parallel using high-throughput genotyping methods, then accurate identification and discrimination of biological samples is achieved, but the analysis becomes time-consuming and complex
Solution Approach 1:
The patent extracts and identifies a specific subset of informative SNPs from the complete set of potential SNPs. By selecting only those SNPs that provide meaningful discrimination power for the particular biological samples being analyzed, the method reduces the analysis from hundreds or thousands of SNPs to a manageable panel while maintaining identification accuracy
Solution Approach 2:
The patent applies local quality by tailoring the SNP panel to the specific characteristics of the biological samples being analyzed. Different sample types (e.g., cell lines, tumor samples, blood samples) receive customized SNP panels selected based on their genetic variability and discriminatory power for that particular sample set, rather than using a uniform approach for all samples
2Measurement precision
If hundreds or thousands of SNPs are analyzed in parallel, then comprehensive genetic characterization is achieved, but the analysis becomes costly and inefficient
Solution Approach 1:
The method extracts only the essential SNPs needed for accurate sample identification from the complete SNP set. By removing redundant SNPs that do not contribute meaningfully to discrimination, the analysis becomes more efficient and cost-effective while preserving the ability to accurately distinguish between biological samples
Solution Approach 2:
The patent applies partial action by analyzing only the necessary subset of SNPs rather than the complete set. This selective approach performs sufficient genetic analysis to achieve accurate identification without the excessive cost and time associated with comprehensive genotyping of all available SNPs
3Measurement precision
If a large number of SNPs are used for genetic analysis, then thorough discrimination among samples is achieved, but the cost-effectiveness decreases
Solution Approach 1:
The patent extracts a minimal sufficient set of SNPs that provides adequate discrimination power for the specific sample set. By identifying and removing unnecessary SNPs from the analysis panel, the method reduces the quantity of genetic markers needed while maintaining the ability to thoroughly discriminate among biological samples
Solution Approach 2:
The patent changes the parameter of SNP panel size from a fixed large number to a variable optimized size based on the specific samples being analyzed. Through statistical analysis, the method determines the optimal number of SNPs needed for each sample set, reducing the quantity analyzed while preserving discrimination power
Data Source
AI summary
Described are methods for identifying single nucleotide polymorphism (SNPs) that are useful for analyzing genetic samples, and for using said SNPs to determine genetic identity of samples.