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A PLS-based multi-disturbance integrated gene selection and tumor-specific gene subset recognition method

A gene selection and identification method technology, applied in the intersection of computing science and life science, can solve the problem of insufficient insight into the whole picture of complex genetic mechanisms, and achieve the effect of reliable molecular diagnosis and treatment, strong discrimination ability, and small length

Active Publication Date: 2018-12-18
FUQING BRANCH OF FUJIAN NORMAL UNIV
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Problems solved by technology

Clearly, the resulting individual gene subsets are often insufficient to gain insight into the full picture of complex genetic mechanisms

Method used

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  • A PLS-based multi-disturbance integrated gene selection and tumor-specific gene subset recognition method
  • A PLS-based multi-disturbance integrated gene selection and tumor-specific gene subset recognition method
  • A PLS-based multi-disturbance integrated gene selection and tumor-specific gene subset recognition method

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Embodiment Construction

[0046] The present invention will be further described below in combination with implementation modes and examples.

[0047] Such as figure 1 As shown, this embodiment provides a PLS-based multi-perturbation integrated gene selection and identification method for tumor-specific gene subsets, including the following steps:

[0048] Step S1: Establish a multi-response variable PLS model, use the SIMPLS algorithm to solve the multi-response variable PLS model, and realize polygenic measurement based on PLS;

[0049] Step S2: Using the PLS-based multi-gene measurement method, under the framework of multi-perturbation integrated gene selection, perform gene selection based on PLS integration on the sample data, and obtain the gene list of the sample data;

[0050] Step S3: Using the base classifier, identify the top k genes with the highest recognition rate from the above sorted gene list to form a tumor-specific gene subset.

[0051] In this example, gene selection is from the o...

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Abstract

A PLS-based multi-disturbance integrated gene selection and tumor-specific gene subset recognition method features that different disturbance mechanisms are introduced to analyze gene selection of multi-disturbance integrate according to characteristics of tumor microarray data. Based on this framework, a new integrated gene selection method based on PLS is developed by using PLS polygenic metrics. On the one hand, the method of the invention is based on the whole effect of the subset, and can quickly identify the genes with differential expression, and also can identify the genes with weak differential expression signal; on the other hand, the method of the invention is based on a multiple disturbance mechanism, and can identify a series of different subsets of genes with small length andstrong discrimination ability. Therefore, the method of the invention can identify a series of different gene subsets and weakly differentially expressed genes, through which the specific expressionpattern of tumor genes can be more comprehensively recognized.

Description

technical field [0001] The invention relates to the interdisciplinary technical field of computing science and life science, in particular to a PLS-based multi-perturbation integrated gene selection and tumor-specific gene subset identification method. Background technique [0002] Tumor is a complex genetic disease, which is caused by abnormal expression of intracellular genes due to DNA damage on some chromosomes, and is a complex disease characterized by uncontrolled cell growth, lack of differentiation and abnormal proliferation. Tumor gene microarray (Microarray) can explore and explain the occurrence, development and formation of complex and diverse tumor diseases at the molecular level. For high-throughput gene expression profile data, machine learning and other technologies can be used to identify specific genes and their functions related to complex tumor diseases, which is of great significance for studying the disease mechanism of tumors and predicting the disease...

Claims

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Application Information

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IPC IPC(8): G06F19/18
Inventor 游文杰甘胜进
Owner FUQING BRANCH OF FUJIAN NORMAL UNIV
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