GSE221521: Differentially Expressed Genes in Diabetic Retinopathy

A 94.6 KB Excel file containing differentially expressed genes (DEGs) identified in the GSE221521 transcriptome dataset. The data was generated by author Haiming Liang and last updated on 2026-06-02. It focuses on uric acid-related genes in diabetic retinopathy, identifying MMP15 and FOXK1 as potential key genes.

Use Cases

• Validate potential biomarkers for diabetic retinopathy based on the identified key genes MMP15 and FOXK1.
• Perform gene set enrichment analysis (GSEA) based on the described enrichment pathways for MMP15 and FOXK1.
• Investigate immune cell infiltration correlations in diabetic retinopathy based on the analysis of 7 immune cell types.
• Study transcriptional regulation by analyzing the 12 transcription factors, such as HOXB7, that target the identified genes.

Strengths

• Data is licensed under CC-BY-4.0, allowing for open sharing and adaptation.
• The description provides specific biological findings, including two identified key genes (MMP15, FOXK1) and 12 associated transcription factors.
• The file size of 94.6 KB suggests a focused, manageable dataset for targeted analysis.

Limitations

• Row count is unknown, which may limit suitability assessment for large-scale modeling.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small (94.6 KB), indicating a limited scope focused on specific analysis results rather than raw expression data.

Provenance

Source

figshare, author Haiming Liang.

Collection Method

Generated via differential expression analysis, machine learning, and ROC analysis of public database transcriptome data (GSE221521), with clinical validation via RT-qPCR.

Freshness

Last updated 2026-06-02 17:32:42; freshness should be verified.