Fig 1.
Schematic illustration of the overall general workflow of this study.
Fig 2.
Volcano plots and Venn diagram depicts the shared DEGs among COVID-19 and ICC.
Volcano plots of (A) COVID-19 and (B) ICC, with genes with |log2Fold Change| > 1 and FDR < 0.05. (C) The Venn diagram depicts the shared DEGs among COVID-19 and ICC.
Table 1.
Overview of datasets with their geo-features and their quantitative measurements in this analysis.
Fig 3.
Analysis of common DEGs between COVID-19 and ICC using ontology and pathway enrichment.
Ontological analysis: (A) Biological processes, (B) Molecular function, and (C) Cellular components. Pathway enrichment analysis: (D) KEGG, (E) Wikipathways, (F) Reactome, and the (G) Bioplanet.
Table 2.
Ontological analysis of common DEGs between COVID-19 and ICC.
Table 3.
Pathway enrichment analysis of common DEGs between COVID-19 and ICC.
Fig 4.
PPI network of common DEGs between COVID-19 and ICC.
The circular nodes in the figure stand in for DEGs, while the edges indicate node interactions. The PPI network consists of 177 edges and 65 nodes. String was used to create the PPI network, and Cytoscape was used to display it.
Fig 5.
Determination of hub genes from the PPI network by using the Cytohubba plugin in Cytoscape.
Hub genes were obtained using the Cytohubba plugin. Here, the red nodes indicate the highlighted top 10 hub genes and their interactions with other molecules. The network consists of 35 nodes and 144 edges.
Fig 6.
Interaction network of hub-gene-TFs.
The cohesive regulatory interaction network of hub-gene-TFs obtained from the Network Analyst and described by Cytoscape. Herein, the green nodes are TFs, and the yellow nodes are hub genes.
Fig 7.
The gene-disease association network represents diseases associated with common genes.
The diseases are depicted by the square node and gene symbols are defined by the circle node.
Table 4.
The recommended drugs for COVID-19 and ICC.