Identification of prognostic apoptosis-related DEGs in the TCGA dataset

The expression of Args was screened from the TCGA expression matrix. The average value of repetitive genes was taken; the abnormal values were deleted. Through Wilcoxon-test, the genes with p < 0.05 were selected as DEGs. We used Univariate Cox analysis to combine the expression of Args with survival time and survival status of HCC patients to screen out PRGs. The screening condition was p < 0.05. The DEGs and PRGs were intersected to select the Args, which were not only differentially expressed between HCC tissues and adjacent normal tissues but also related to the prognosis of HCC. The protein-protein interaction network was drawn by STRING database (version11.0) (https://string-db.org/) to clarify the interaction of the proteins, and the expression correlation coefficient diagram was drawn by R package igraph to show the expression relationship of the genes. R package pheatmap was used to illustrate the expression heatmap to show the expression of the intersect ARGs. The correlation filtering threshold is 0.2. R package survival was used to clarify the relationship between the genes and the prognosis of HCC patients. The screening condition was p < 0.05, as well.

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