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Identification method of markers of esophageal squamous cell carcinoma based on difference analysis of network indicators

A technology of esophageal squamous cell carcinoma and identification method, which is applied in the field of bioinformatics, can solve the problems of low accuracy, insignificant effect, and is easily affected by data noise, and achieves the effect of improving accuracy

Active Publication Date: 2020-06-12
ZHENGZHOU UNIVERSITY OF LIGHT INDUSTRY
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Problems solved by technology

Such gene-based differential expression analysis methods are mostly limited to statistical difference testing. Although such methods are simple and effective, they can only detect the differential expression of a single gene in different samples, and cannot reflect the gene expression network as a whole. The difference in expression, the accuracy is not high and it is easily affected by data noise, which has certain limitations
When identifying differentially expressed genes in a gene network, the indicators selected by such methods are relatively single, which can only measure the criticality and influence of network nodes, and the effect is not obvious in finding differentially expressed genes, and only mine gene expression at the global level Differences in gene expression in local network communities cannot be identified

Method used

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  • Identification method of markers of esophageal squamous cell carcinoma based on difference analysis of network indicators
  • Identification method of markers of esophageal squamous cell carcinoma based on difference analysis of network indicators
  • Identification method of markers of esophageal squamous cell carcinoma based on difference analysis of network indicators

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Embodiment 1

[0040] Based on the above formula, a method for identifying markers of esophageal squamous cell carcinoma based on network index difference analysis of the present invention will be described below in conjunction with specific embodiments, including the following steps:

[0041]Step 1: download the data set numbered GSE23400 in NCBI, which includes data sets from two different chips (Affymetrix U133A / B chip), the present invention selects the probe data on chip B for data processing, chip B It contains 51 esophageal squamous cell carcinoma sample data and corresponding 51 normal sample data (two interfering probe data are discarded in each sample). The processing of the two sample data is as follows:

[0042] (1) use Expression Console TM Software standardizes the data;

[0043] (2) Convert each data to P-value and robust average signal value by MAS5.0 method;

[0044] (3) Delete the probe data without corresponding genes, and then filter out the genes that are hardly ex...

Embodiment 2

[0098] Example 2 Reliability Verification of Gene Interaction Network

[0099] In order to verify the reliability of the established network relationship, the expression data of some samples were randomly selected, and the Spearman correlation between each gene was still calculated, and a repeatability test was performed. If most of these network relationships can still be found in the subset of samples, it shows that the network relationships we have established are relatively reliable.

[0100] 45 gene sample data were randomly selected from the two sample data of the experimental group, and the intergenic correlation coefficient was calculated according to the gene expression array, and all relationship pairs with a correlation coefficient>=0.8 were screened out as the verification group, and compared with the experimental group. The relationship pairs were compared, and a fixed number of gene relationship pairs were taken for each, and the repetition rate was calculated. R...

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Abstract

The invention belongs to the technical field of bioinformatics, and relates to a method for identifying esophageal squamous cell carcinoma markers on the basis of network index difference analysis. The method comprises the following steps of processing esophageal squamous cell carcinoma gene sample data and normal gene sample data to construct an esophageal squamous cell carcinoma gene interactionnetwork and a normal gene interaction network; using a network module identification method to find out key community structures in the two networks, and performing gene function enrichment analysison the key community structures; extracting same nodes from the two networks, and retaining nodes linked to the same nodes to obtain the two simplified networks; using a global index and a local modular index, analyzing the two simplified networks to obtain genes related to esophageal squamous cell carcinoma; combining a gene function enrichment analysis result with gene annotations and functionalreferences to finally determine candidate markers for diagnosis of esophageal squamous cell carcinoma. A method for studying the esophageal squamous cell carcinoma markers on the basis of gene network difference analysis is further perfected.

Description

technical field [0001] The invention belongs to the technical field of bioinformatics, and relates to a method for identifying markers of esophageal squamous cell carcinoma based on network index difference analysis. Background technique [0002] The pathological types of esophageal cancer are mainly esophageal squamous cell carcinoma (ESCC) and adenocarcinoma (Esophagus adenocarcinoma, EAC), and the distribution of pathological types in different regions is different. The pathogenesis of esophageal cancer involves a variety of molecular changes, including DNA, RNA, and protein, accompanied by a series of biological function changes, such as cell proliferation, signaling, transmission, and metabolic regulation disorders. After a multi-stage evolution process, the final develop into cancer. Due to the lack of early accurate diagnosis of esophageal cancer and the limitations of prevention and treatment methods, once the patients are found to be in the middle and late stage, t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16B20/00G16B25/10
CPCG16B20/00G16B25/00
Inventor 姜素霞王延峰姜利英孙军伟张启樊继辉张俊明
Owner ZHENGZHOU UNIVERSITY OF LIGHT INDUSTRY
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