Flow cytometry data gating method and system, storage medium and electronic equipment

Abstract

The invention discloses a flow cytometry data gating method and system, a storage medium and electronic equipment, and the method comprises the following steps: carrying out the standardized conversion of original data, generating a binary image related to the distribution of data points based on the converted data, and calculating and determining the number and positions of clustering centers, obtaining a contour boundary corresponding to the clustering center and mapping the contour boundary to the original data to generate an initial gating curve; and obtaining the convex hull contour of the clustering cluster through the local density and distance of the data points to correct the edge of the initial gating curve to form a final gating curve. According to the gating method, a binary image is generated according to original data, the number and positions of clustering centers are rapidly obtained through the binary image, and an initial gating curve is generated. The embodiment of the invention provides the flow cytometry data gating method and system, the storage medium and the electronic equipment. The gating method has the characteristics of high gating precision and short operation 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 cytometer 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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