Data Sheet 9_Transcriptomic and experimental identification of immune- and telomere-relate

Data Sheet 9 contains transcriptomic and experimental data from a study identifying immune- and telomere-related biomarkers for pelvic organ prolapse (POP). The dataset, authored by Rong Ma and shared on figshare, includes results from differential expression analysis, machine learning, and validation via RT-qPCR, pinpointing CCNL1 and NAMPT as key genes. It was last updated on May 22, 2026.

Use Cases

• Validating the diagnostic potential of CCNL1 and NAMPT biomarkers based on the reported ROC analysis and nomogram.
• Exploring molecular regulatory networks based on the predicted interactions with 21 key nodes and 28 interactions.
• Identifying potential therapeutic compounds based on the drug prediction results for 14 compounds.
• Conducting pathway enrichment analysis based on the reported enrichment in ubiquitin-mediated proteolysis and other pathways.

Strengths

• Includes results from multiple analytical methods: differential expression analysis of 864 genes, machine learning, and experimental validation via RT-qPCR.
• Identifies two specific key biomarkers (CCNL1 and NAMPT) with reported statistical significance (p < 0.05) and diagnostic AUC (0.847).
• Released under a permissive CC-BY-4.0 license, allowing for broad reuse with attribution.

Limitations

• Dataset is very small (2.5 KB), suggesting it contains summary or processed results rather than raw transcriptomic data.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for certain analyses.

Provenance

Source

Rong Ma via figshare.

Collection Method

Analysis of public-database transcriptome data using immune infiltration, WGCNA, differential expression, machine learning, and experimental validation.

Freshness

Last updated 2026-05-22 06:10:49; freshness should be verified.