Schizophrenia Fatty Acid Metabolism Gene Expression and Diagnostic Model

A dataset containing results from a study on cell type-specific alterations in fatty acid metabolism-related genes in schizophrenia. The data likely includes key genes identified from single-cell and bulk RNA-seq analysis of 9 patients and 14 controls, and a five-gene diagnostic model. The dataset was authored by Cui Zhao and last updated on 2026-04-21.

Use Cases

• Training diagnostic classifiers based on the five key genes (ACAA1, ACAT2, ACSS1, PSME1, S100A10).
• Analyzing gene expression correlations with inflammatory responses in neuronal cells.
• Validating single-cell RNA-seq findings in bulk RNA-seq cohorts like GSE174407 and GSE107638.

Strengths

• Includes a diagnostic model with an AUC of 0.856 in the training cohort and 0.779 in validation.
• Integrates data from multiple sources: single-cell sequencing (9 SCZ, 14 controls) and two bulk RNA-seq datasets.
• Key findings were validated in an MK-801-induced mouse SCZ model with p < 0.001 significance.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare, authored by Cui Zhao.

Collection Method

Integration of single-cell and bulk RNA-seq data, with analysis using Seurat, SCENIC, Monocle 2, and LASSO regression.

Freshness

Last updated 2026-04-21 05:30:01; freshness should be verified.