Comparison Of Normalization Methods And Weighted Co-expression Network Analysis Based On MiRNA Microarray Data

MiRNA is a type of non-coding single-stranded RNA molecules with a length of about 18-25 nucleotides.MiRNA is widely found in eukaryotic cells.In recent years,researchers have found that miRNA participates in many biological processes,such as cell cycle,cell development,cell proliferation,gene expression and so on.In the process of in-depth research on the relationship between miRNA and cancer,it has been found that miRNA plays an important role in promoting or inhibiting the development of cancer.In this paper,miRNA expression data of gastric cancer was used as the research object to carry out follow-up research and analysis.Gastric cancer is one of the most common malignant tumors in the world.Among all cancers,the incidence rate of gastric cancer ranks fifth and the mortality rate ranks third.The early clinical symptoms of gastric cancer are not obvious,many patients diagnosed were in the middle or late stages.Its prognosis is poor,therapy is very difficult and mortality is enormous high.So far,there is no effective treatment for gastric cancer.The 5-year survival rate of patients with advanced gastric cancer is less than 20%.China is also a high incidence area of gastric cancer.Therefore,studying the pathogenesis of gastric cancer is conducive to the prevention,diagnosis and treatment of gastric cancer.Many research results show that miRNA is closely related to the occurrence of gastric cancer.In the first part,the effects of six normalization methods on miRNA microarray expression data were compared and analyzed.Because there are dimensional differences and systematic errors in miRNA microarray data,we need to normalize miRNA microarray data before studying the relationship between miRNA and gastric cancer.There are many normalization methods.In order to ensure the accuracy of the subsequent analysis results,we need to choose the best one.This study involves six common normalization methods,namely,global normalization,locally weighted regression method,quantile normalization,trimmed mean method,variance stabilizing normalization and scale normalization method.We choose K-S test and mean square error as the measurement standards.We use six normalization methods to normalize the miRNA microarray data,and compare the influence of six normalization methods on the miRNA microarray expression data.MA chart and box chart are used to show the influence of six normalization methods on the distribution of miRNA microarray data.Secondly,K-S test and mean square error are used to analyze the excellence of the six normalization methods.Finally,the research shows that in terms of miRNA microarray data,the results of local weighted regression method and quantile normalization method are better than the other four methods,and locally weighted regression method is the best.In the second part,the functional modules of miRNA expression data are identified based on weighted gene co-expression network analysis(WGCNA)method.In this chapter,the miRNA expression data of gastric cancer in TCGA database are used for research and analysis.The weighted co-expression network is constructed by WGCNA algorithm to select the miRNA modules significantly related to gastric cancer.In addition,GO enrichment analysis and biological pathway analysis were carried out for the miRNA module.It was found that the miRNA co-expression module involved in the following pathways: Beta1 integrin cell surface interactions,ErbB receptor signaling network,Glypican pathway,proteoglycan syndecan-mediated signaling events,tumornecrosis factor related apoptosis inducing ligand signaling pathway,integrin family cell surface interactions,endothelins,plasma membrane estrogen receptor signaling,vascular endothelial growth factor and its vascular endothelial growth factor receptor signaling network,IFN-gamma pathway and so on.In order to compare the gene ontology enrichment analysis and biological pathway analysis of the co-expression module,we screened differentially expressed miRNA from the obtained miRNA expression data and conducted gene ontology enrichment analysis and biological pathway analysis on them.The result showed that the main biological pathways involved in the differential expression of miRNA were as follows: Beta1 integrin cell surface interactions,ErbB receptor signaling network,Glypican pathway,tumor necrosis factor-related apoptosis inducing ligand signaling pathway,vascular endothelial growth factor and its receptor-mediated signaling network,syndecan-1-mediated signaling events sphingosine-1-phosphate pathway,endothelins,proteoglycan syndecan-mediated signaling events and plasma membrane estrogen receptor signaling and so on.By comparing the results of the analysis of the two biological pathways,we found eight common biological pathways related to gastric cancer.Namely,?1 integrin cell surface interactions,ErbB receptor signaling network,Glypican pathway,tumor necrosis factor-related apoptosis inducing ligand signaling pathway,vascular endothelial growth factor and its receptor signaling network,endothelins,proteoglycan syndecan-mediated signaling events and plasma membrane estrogen receptor signaling,which provide a new direction for clinical diagnosis of gastric cancer.