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Multi-layer network model construction method and application with cancer-related SNP, gene, miRNA and protein interaction

A multi-layer network, construction method technology, applied in the fields of bioinformatics, biological systems, instruments, etc., can solve the problems of inability to obtain correlations and insufficient detection of genetic variants

Active Publication Date: 2019-02-12
HARBIN INST OF TECH SHENZHEN GRADUATE SCHOOL
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Problems solved by technology

Therefore, GWAS is insufficient to detect genetic variants with small marginal effects, and cannot obtain the correlation between SNP locus-gene expression data-miRNA data-protein data

Method used

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  • Multi-layer network model construction method and application with cancer-related SNP, gene, miRNA and protein interaction
  • Multi-layer network model construction method and application with cancer-related SNP, gene, miRNA and protein interaction
  • Multi-layer network model construction method and application with cancer-related SNP, gene, miRNA and protein interaction

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Embodiment 1

[0085] The genome-wide VCF data of breast cancer comes from the breast cancer laboratory database of the University of Cambridge. The downloaded data has a total of 1011 cases, including 640 breast cancer patients and 371 healthy controls. The breast cancer expression level data used to construct the network comes from the TCGA cancer database. Download RNA-Sequencing (hereinafter referred to as gene expression data), miRNASeq (hereinafter referred to as miRNA expression data) and protein expression data of breast cancer patients. For details, see Table 1.

[0086] Table 1 Tumor marker data description table

[0087]

[0088] The amount of gene expression data is 1214×24991 (the number of tumor tissue samples is 1101, the number of normal tissue samples is 113; 24991 is the gene type); the amount of miRNA expression data is 1200×1882 (the number of tumor tissue samples is 1096, and the number of normal tissue samples The number is 104; 1882 are miRNA types); the amount of...

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Abstract

The invention provides a multi-layer network research method and application with cancer-related SNP, gene, miRNA and protein interaction and belongs to the technical field of cancer bioinformatics analysis. The method comprises steps that 1), significantly different SNP locus data between a cancer tissue sample and a normal tissue sample are screened; 2), the xgboost method is utilized to separately analyze the cancer tissue sample and the normal tissue sample to obtain significantly different gene expression data, miRNA data and protein data; 3), the significantly different SNP locus data, the gene expression data, the miRNA data and the protein data are respectively taken one layer, and the maximum information coefficient method MIC is utilized to analyze the relationship between the two; and 4), the SNP locus-gene expression data-miRNA data-protein data multi-layer network association relationship is obtained. The method is advantaged in that a tumor marker can be accurately analyzed.

Description

technical field [0001] The invention belongs to the technical field of bioinformatics analysis of cancer, and in particular relates to a multi-layer network model construction method and application of cancer-related SNP, gene, miRNA and protein interactions. Background technique [0002] Cancer is one of the major diseases and serious public health problems that seriously threaten human survival and social development. Cancer control has become the health strategy focus of governments around the world. With the increasing maturity of gene sequencing technology and the in-depth study of genomics, bioinformatics scientists have identified multiple genetic variations related to complex diseases through genome-wide association analysis (GWAS) technology. GWAS technology relies on a single SNP locus as a genetic marker to conduct control or correlation exploration on the whole genome in order to find SNP loci that significantly affect the phenotype. GWAS has achieved great succ...

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Application Information

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IPC IPC(8): G16B5/00
Inventor 张阳赵毅王德华
Owner HARBIN INST OF TECH SHENZHEN GRADUATE SCHOOL
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