Single Cell Classification via SNP Genotyping
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Solution Overview
Problem
Current single cell classification methods are limited by high cytotoxicity, lack of specific markers for certain cell subgroups, and low sensitivity, leading to inaccurate classification and detection.
Innovation Solution
A method using next-generation sequencing (NGS) technology to classify single cells by sequencing whole genomes, aligning reads to a reference genome, filtering data, determining consistent genotypes, and selecting SNP sites associated with cell mutation for accurate classification without labeling cells.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical and mechanical, chemical or biological methods (flow cytometer, magnetic cell sorter) are used for single cell classification, then cells can be sorted by phenotype determination, but the sensitivity of subgroup classification and detection is low and specificity is disputed
Solution Approach 1:
The patent replaces physical and mechanical classification methods (flow cytometer, magnetic cell sorter) with a biochemical method based on SNP genotyping. Instead of using fluorescent dyes, antibodies, and mechanical sorting, the invention uses DNA sequencing and genetic marker analysis to classify single cells, thereby eliminating the limitations of phenotype-based methods and achieving higher sensitivity and reliability
Solution Approach 2:
The patent changes the classification parameter from phenotypic characteristics (cell size, surface area, fluorescence intensity) to genotypic characteristics (SNP alleles). This parameter change enables precise identification of cell subgroups based on genetic variation, resolving the issues of low sensitivity and disputed specificity associated with phenotypic methods
2Measurement precision
If fluorescent dyes and antibodies are used for cell labeling and sorting, then specific cell subgroups can be identified, but the cytotoxicity is high and sample preparation is cumbersome
Solution Approach 1:
The patent replaces the biochemical labeling system (fluorescent dyes, antibodies) with a DNA-based identification system. Instead of attaching external markers to cell surfaces, the invention directly sequences the genomic DNA of single cells and identifies cell subgroups through SNP genotyping, eliminating cytotoxicity and simplifying sample preparation
Solution Approach 2:
The patent extracts and analyzes the genomic DNA of single cells to obtain SNP genotype information for classification. By taking out and analyzing the genetic material directly, the invention avoids the need for cell surface labeling and reduces harmful effects on cell viability
3Quantity of substance
If phenotype determination methods are used for statistical analysis, then cell characteristics can be measured, but the accuracy of cell subgroup classification is insufficient
Solution Approach 1:
The patent changes the measurement parameter from phenotypic characteristics (cell size, shape, surface area) to genotypic characteristics (SNP allele frequencies). This parameter change provides more accurate and stable classification because genetic markers are inherent to the cell lineage and do not change with cell state or environmental conditions
Solution Approach 2:
The patent uses SNP genotypes as an intermediary to infer cell subgroup membership. Instead of directly measuring phenotypic characteristics and attempting to classify based on those measurements, the invention uses stable genetic markers as intermediaries that reliably indicate cell lineage and subgroup identity
Data Source
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AI summary
Provided are a single cell classification method, a gene screening method and a device for implementing the method. In that, the single cell classification method includes the following steps: sequencing the whole genomes of a plurality of single cell samples from the same group, respectively, so as to obtain reads from each single cell sample; aligning the reads from each single cell sample to the sequence of a reference genome, respectively, and performing data filtering on said reads; on the basis of the filtered reads, determining a consistent genotype of each single cell sample, in which consistent genotypes of all the single cell samples constitute an SNP dataset of said group; aimed at said each single cell, on the basis of the SNP dataset of said group, determining a corresponding genotype for each cell at a site corresponding to a position in an SNP dataset of the reference genome; and selecting an SNP site associated with cell mutation, and on the basis of the genotype of said single cell at the site, classifying said single cell.