Biomarker selecting method based on meta-analysis, and system

Abstract

The invention discloses a biomarker selecting method based on meta-analysis, and a system. The method comprises the following steps of selecting original sequencing data; performing mapping analysis on the original sequencing data by means of an FANSe algorithm, obtaining gene quantification information and setting a gene original group; calculating an importance sequence of the gene in the original group according to a GWGS algorithm, integrating the importance of each group of genes according to a GWRS algorithm, obtaining an integrated gene importance arrangement list, sequencing the genes according to the importance from highest to lowest; performing data mining by means of a Wrapper Feature Selection model based on the SVM, differentiating a data sample type, and screening the biomarker from the gene with high importance. According to the method, multi-center original sequencing data are integrated according to the characteristic of the sequencing data, and system differences in platform, sample and experiment designing are settled; an integrating analysis algorithm with high robustness is used for performing deep data mining, thereby mining common, specific and key biomacromolecules.

Description

technical field [0001] The invention relates to the technical field of biomarker detection, in particular to a biomarker selection method and system based on integrated analysis. Background technique [0002] Finding more common, specific, and critical biomacromolecules (including nucleic acids and proteins) can improve the effect of medical treatment, but the existing molecular markers are difficult to meet the common, specific, and critical requirements, and most of the molecular markers use Multi-center data analysis is obtained, while the existing multi-center data routine processing method is to use Meta-analysis (meta-analysis) to integrate the conclusions of multi-center research, because multi-center data often have inconsistent factors such as differences in experimental subjects, differences in instrument methods, etc. , the method of indiscriminately merging the original data for analysis is not appropriate, and the meta-analysis is prone to bias due to factors su...

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Problems solved by technology

[0002] Finding more common, specific, and critical biomacromolecules (including nucleic acids and proteins) can improve the effect of medical treatment, but the existing molecular markers are difficult to meet the common, specific, and critical requirements, and most of the molecular markers use Multi-center data analysis is obtained, while the existing multi-center data routine processing method is to use Meta-analysis (meta-analysis) to integrate the conclusions of multi-center research, because multi-center data often have inconsistent factors such as differences in experimental subjects, differences in instrument methods, etc. , the method of indiscriminately merging the original data for analysis is not appropriate, and the meta-analysis is prone to bias due to factors such as the quality of the original data, the analysis level of the original researchers, and the errors and omissions of the original research tools, so that a large amount of precious data cannot be obtained. Take advantage of

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