Question

How to manage self loop in gene coexpression network constructed using Pearson correlation in Cor() function

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Hai, I have a control vs treated RNA-seq plant data for which I am trying to construct gene coexpression network.I identifed a total of 6000 genes are significantly differential expressed genes using DESeq2 R package after applying FDR cutoff 0.05. The normalised count matrix of these 6000 genes derived after rlog transformation was inputed to Cor() function and Pearson correlation was applied. The pair wise correlation analysis gave ~30 million gene pairs out of which, 1380285 gene pairs were selected with a cutoff >0.95 correlatio and were visualized using cytoscape While visualizing the network in cytoscape. I observed self loop for all genes in the network. 1.) Is the presence of self loop for all genes is biologically correct or not. 2.) If it's not correct, how to avoid self loops in all genes in the network and retain only the biologically significant one's

rna-seq gcn desq2 pearsoncorrelation • 885 views

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