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Tumor screening model, its construction method and device

A technology for tumor screening and construction methods, applied in character and pattern recognition, instrumentation, sequence analysis, etc., can solve problems such as difficult to achieve low-cost tumor screening, and achieve the effect of efficient screening and detection

Active Publication Date: 2021-11-19
北京橡鑫生物科技有限公司 +2
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0006] The main purpose of the present invention is to provide a tumor screening model, its construction method and device, so as to solve the problem that it is difficult to realize low-cost tumor screening in the prior art

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  • Tumor screening model, its construction method and device
  • Tumor screening model, its construction method and device

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Embodiment 1

[0039] In a preferred embodiment of the present application, a method for constructing a tumor screening model is provided, figure 1 is a flowchart of a method for constructing a tumor screening model according to an embodiment of the present invention. As shown, the method includes:

[0040] Step S101, obtaining two sets of cell-free DNA sequencing data, the two sets of cell-free DNA sequencing data are respectively from multiple positive samples and multiple control samples;

[0041] Step S103, comparing two sets of cell-free DNA sequencing data and screening out the specific characteristics of ctDNA fragments;

[0042] Step S105, using the specific features of ctDNA fragments to construct a machine learning model to obtain a tumor screening model.

[0043] The above-mentioned method of the present application can be used to greatly improve the detection of ctDNA according to the characteristic distribution of ctDNA fragments which are obviously different from cfDNA, and f...

Embodiment 2

[0069] In a preferred embodiment of the present application, a more specific method for constructing a tumor screening model is provided, the method comprising:

[0070] 1. The input data is the raw data of next-generation sequencing off-machine, and the data format is fastq.

[0071] 1) Preprocess the original off-machine data, including removing adapters and low-quality data.

[0072] 2) Compare and sort the processed original off-machine data with the reference genome, and obtain the comparison results, and the data format is bam.

[0073] 3) Perform duplication reads identification on the bam file, and remove duplication reads.

[0074] 2. Feature selection:

[0075] A) Compare the cell-free DNA sequencing data of the two groups of samples and screen out the specific characteristics of the ctDNA fragments according to the following principles:

[0076] 1) Extract the absolute position of the end of all read pairs in the tumor sample, that is, the physical position corre...

Embodiment 3

[0106] In an optional embodiment, a tumor screening model is also provided, and the tumor screening model is constructed by any of the above methods.

[0107] In another optional embodiment, there is also provided a tumor screening device, which contains the above-mentioned tumor screening model.

[0108] The tumor screening model or tumor screening device can be used to greatly improve the detection of ctDNA according to the characteristic distribution of ctDNA fragments that are significantly different from cfDNA, and further screen out the unique characteristics of ctDNA, and make full use of the specificity of ctDNA in positive samples. Sexual characteristics, constructed by machine learning, can be relatively accurate and efficiently screen the samples to be tested. Moreover, the tumor screening model does not require high sequencing depth of the samples to be tested, and can be realized by conventional low-depth sequencing, providing important research directions and cli...

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Abstract

The invention provides a tumor screening model, its construction method and device. The model construction method includes obtaining two groups of cell-free DNA sequencing data from multiple positive samples and multiple control samples; comparing the two groups of cell-free DNA sequencing data and screening out the specific characteristics of ctDNA fragments; using the specific characteristics of ctDNA fragments to perform machine The learning model is constructed to obtain a tumor screening model. According to the feature distribution of ctDNA fragments that are significantly different from cfDNA, it can be used to greatly improve the detection of ctDNA, and make full use of ctDNA-specific features to build a tumor screening model through machine learning. Using this tumor screening model does not require high sequencing depth of the samples to be tested, which can be achieved by conventional low-depth sequencing, providing important research directions and clinical guidance for cancer (early) screening.

Description

technical field [0001] The present invention relates to the field of gene sequencing data analysis, in particular to a tumor screening model, its construction method and device. Background technique [0002] The next-generation sequencing technology is also called massively parallel sequencing. Its core idea is to sequence while synthesizing. It can sequence millions or even billions of DNA molecules at the same time, achieving the goal of large-scale and high-throughput sequencing. The revolutionary advance after Sanger sequencing. In recent years, with the rapid development of next-generation sequencing technology, it has been gradually applied to clinical medical detection and scientific research in the direction of blood tumors. Target sequence capture can selectively isolate or enrich genome-specific fragments, so higher sequencing depth can be obtained at a lower cost, laying a good foundation for low-frequency detection and large data accumulation. At present, in cl...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16B30/00G16B40/00G16H50/20G06K9/62
CPCG16B30/00G16B40/00G16H50/20G06F18/24323
Inventor 张萌萌郭璟楼峰曹善柏
Owner 北京橡鑫生物科技有限公司
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