A 2026 study by Yi Lu analyzes transcriptomic data from two cohorts to identify metabolic reprogramming features in coronary artery calcification. The dataset likely contains differential gene expression results, functional enrichment analyses, and biomarker candidate scores. It was published on figshare under a CC-BY-4.0 license.
Use Cases
- Validate biomarker diagnostic performance based on AUC scores for PXDN and other candidates.
- Analyze metabolic pathway alterations based on gene set enrichment analysis results.
- Explore gene co-expression networks based on Weighted Gene Co-expression Network Analysis (WGCNA) modules.
- Build regulatory network models based on transcription factor and miRNA interactions identified.
- Compare differential gene expression profiles between CAC and control groups.
Strengths
- Includes validation cohort data (GSE211752) alongside discovery cohort (GSE58150).
- Identifies a biomarker candidate (PXDN) with reported AUC of 0.95 in the discovery cohort.
- Provides in vivo validation results from a CAC mouse model.
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 (28.1 KB), indicating limited scope.
Provenance
- Source
- figshare
- Collection Method
- Analysis of transcriptomic datasets GSE58150 and GSE211752.
- Freshness
- Last updated 2026-04-10 06:02:14; freshness should be verified.