Integrated Transcriptomic and Single-Cell Data for Acute Kidney Injury Biomarker Discovery

Transcriptomic and single-cell data from a study identifying pyruvate metabolism-related genes GGT6 and LEAP2 as diagnostic biomarkers for Acute Kidney Injury (AKI). The dataset was created by Xiang Wei and last updated on June 2, 2026. It is a 52.4 KB RAR archive available under a CC-BY-4.0 license on figshare.

Use Cases

• Validate diagnostic biomarkers for AKI based on the identified genes GGT6 and LEAP2.
• Analyze immune cell infiltration patterns in AKI based on the seven cell types mentioned.
• Investigate cell-cell communication networks, particularly between NKT cells and renal tubule cells.
• Study gene expression dynamics during NKT cell differentiation using pseudotime analysis results.

Strengths

• Dataset is derived from integrated public bulk transcriptomic and single-cell datasets, suggesting a multi-source foundation.
• Key findings were validated in a cisplatin-induced AKI mouse model, indicating experimental corroboration.
• The study employed multiple analytical methods including WGCNA, machine-learning screening, and ROC assessment.

Limitations

• The dataset is very small at 52.4 KB, indicating limited scope or processed results rather than raw sequencing data.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale modeling.

Provenance

Source

figshare

Collection Method

Integrated analysis of public bulk transcriptomic and single-cell datasets, with validation in a mouse model.

Freshness

Last updated 2026-06-02 15:12:20; freshness should be verified.