Gating method, system, storage medium and electronic equipment for flow cytometry data

Abstract

The invention discloses a gating method, system, storage medium and electronic equipment for flow cytometer data. The method includes: standardizing and converting the original data, and generating a binary image about the distribution of data points based on the converted data, and calculating Determine the number and position of the cluster centers, obtain the contour boundaries corresponding to the cluster centers and map the contour boundaries to the original data, and generate the initial gating curve; obtain the convex hull contour of the cluster clusters through the local density and distance of the data points to modify the edge of the initial gating curve to form the final gating curve. The gating method generates a binary image based on the original data, and uses the binary image to quickly obtain the number and position of cluster centers and generate an initial gating curve. Embodiments of the present application provide a gating method, system, storage medium, and electronic equipment for flow cytometry data. The gating method has the characteristics of high gating accuracy and short computing time.

Description

technical field [0001] The invention relates to the technical field of flow cytometry data analysis, and mainly relates to a gating method, system, storage medium and electronic equipment for flow cytometry data. Background technique [0002] Flow cytometry is a technique that can accurately and quickly perform multi-parameter quantitative analysis of the physicochemical and biological characteristics of cells and sort specific cell groups. It can detect millions of cells per sample and quickly quantify each Up to 50 parameters of cells. [0003] The outstanding advantage of flow cytometry lies in the high-throughput detection capability of samples. However, the complexity of the data analysis stage is the bottleneck of this technology, which leads to the great potential of flow cytometry has not been fully released. [0004] The gating analysis of flow cytometry data is the process of sample group identification. Through a series of two-dimensional scatter plots generated ...

AI Technical Summary

Problems solved by technology

The strategy of determining the clustering depends on the specific algorithm implementation. In the existing technology, the gate is set based on K-means clustering. Although the calculation speed has advantages, the precision of the gate is relatively low, and it is prone to overfitting when dealing with outlier data. Phenomenon, there are shortcomings of insufficient precision

In the prior art, gating is also based on spectral clustering. This method has improved the accuracy of gating, but it is limited by the mathematical mechanism of matrix product method for result estimation, and the calculation time is too long. Especially when dealing with a large amount of data, the disadvantage is obvious. There is a disadvantage of slow calculation speed

[0009] In general, the existing unsupervised gating methods based on clustering generally have the disadvantages of insufficient gating accuracy or slow operation speed.

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