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Identification of Crucial Degs and Hub Genes in Focal Segmental Glomerulosclerosis: A Bioinformatics Study

Author(s): Bhuvnesh Rai, Prabhakar Mishra, Mehar Hasan Asif and Swasti Tiwari

Aims

In individuals with focal segmental glomerulosclerosis, identify the important differentially expressed genes (DEGs) relative to healthy control, in kidney tissue samples (glomeruli and tubulointerstitium tissue) and examine their probable role in the molecular mechanism and pathogenesis process of disease.

Methods

From the Gene Expression Omnibus (GEO) database, raw microarray data generated from kidney tissues from focal segmental glomerulosclerosis patients, and healthy controls patients (GSE121233, GSE125779, GSE129973) were retrieved. Transcription analysis console 4.0 was used to identify DEGs. FUNRICH (Functional enrichment analysis tools) and Enrichr were used to perform functional gene enrichment analysis. Then, Search Tool for Retrieval Interacting Genes (STRING) 10.0 for PPI analysis and cyto scape's for network visualization was used. Further hub genes were identified using the cytohubbaalogorithm plug-in. Then KEGG and REACTOME databases were integrated with Shiny Go and FUNRICH to perform pathway analysis. We used GSEA analysis and associated pathway enrichment by metascape analysis utilizing the molecular complex identification (MCODE) algorithm to discover densely linked network components to further elucidate the likely mechanism of action of related genes in FSGS. The MCODE networks identified for individual gene lists have been gathered. Pathway and process enrichment analysis has been applied to each MCODE component independently, and the three best-scoring terms by p-value have been retained as the functional description of the corresponding components, shown in the tables underneath corresponding network plots further cross validation was done by ORA (over representation analysis) for the commonly (up-regulated) genes including hubgene from all three datasets was done by webgestalt. Finally, we check the raw expression level of all up regulated DEGs, including hub genes

Journal Statistics

Impact Factor: * 3.0

CiteScore: 2.9

Acceptance Rate: 11.01%

Time to first decision: 10.4 days

Time from article received to acceptance: 2-3 weeks

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    Editor In Chief

    Jean-Marie Exbrayat

  • General Biology-Reproduction and Comparative Development,
    Lyon Catholic University (UCLy),
    Ecole Pratique des Hautes Etudes,
    Lyon, France

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