Six signature genes (FKBP15, EHMT1, CHPT1, KLC1, SCPEP1, CFD) identified as potential pathogenic markers for a monocyte subset in myasthenia gravis. The dataset was generated by Shuang Li through multi-omics integration and machine learning analysis and was last updated on May 1, 2026. The file is 1.5 KB in size.
Use Cases
- Validate monocyte subset markers based on the six identified signature genes.
- Investigate CFD expression patterns in disease progression based on the description of its elevated levels.
- Analyze pathway associations (e.g., mTORC1 signaling, complement) for high TWAS activity subsets.
- Benchmark machine learning models for feature selection in immunology based on the seven algorithms used.
- Study intercellular communication activity differences between CFD+ and CFD- monocytes.
Strengths
- Identifies six specific signature genes (FKBP15, EHMT1, CHPT1, KLC1, SCPEP1, CFD).
- Integrates data from multiple authoritative sources (GEO, GWAS catalog, GTEx).
- Includes validation from original scRNA-seq data on MG patient peripheral blood.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- The dataset is very small (1.5 KB), indicating limited scope.
Provenance
- Source
- figshare
- Collection Method
- Multi-omics integration of scRNA-seq, GWAS summary, and expression quantitative trait loci data, followed by machine learning analysis.
- Freshness
- Last updated 2026-05-01 05:25:25; freshness should be verified.