Data Sheet 12_Transcriptomic and experimental identification of immune- and telomere-relat

A 2026 computational study by Rong Ma identifies key biomarkers for pelvic organ prolapse (POP). The dataset contains results from differential expression analysis, machine learning, and validation, pinpointing CCNL1 and NAMPT as candidate genes. It is a 5.2 KB CSV file shared under a CC-BY-4.0 license on figshare.

Use Cases

• Biomarker validation for pelvic organ prolapse based on identified key genes CCNL1 and NAMPT.
• Pathway enrichment analysis based on results from Gene Set Enrichment Analysis (GSEA) mentioned in the description.
• Drug target prediction based on the 14 potential therapeutic compounds identified.
• Diagnostic model development based on the nomogram with an AUC of 0.847 described in the study.

Strengths

• Includes 864 differentially expressed genes identified from transcriptome data.
• Key biomarkers CCNL1 and NAMPT were validated by RT-qPCR with statistical significance (p < 0.05).
• The diagnostic nomogram model achieved an AUC of 0.847.
• A molecular regulatory network was constructed with 21 key nodes and 28 interactions.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 5.2 KB, indicating limited scope.

Provenance

Source

figshare, author Rong Ma.

Collection Method

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

Freshness

Last updated 2026-05-22 06:10:50; freshness should be verified.