Table 10_CFD+CD14+ monocytes: potential pathogenic subset in myasthenia gravis uncovered b

A multi-omics integration study identified six signature genes in a potential pathogenic monocyte subset for myasthenia gravis. The dataset contains results from transcriptome-wide association studies and single-cell RNA sequencing analyses of peripheral blood from patients and healthy controls. The data was authored by Shuang Li and last updated on 2026-05-01.

Use Cases

• Validate monocyte-related signature genes based on the six identified genes (FKBP15, EHMT1, CHPT1, KLC1, SCPEP1, CFD).
• Investigate cell-type-specific TWAS activity based on the analysis of CD14+ monocytes.
• Benchmark machine learning feature selection algorithms based on the seven algorithms used in the study.
• Study pathway enrichment in immune cells based on the mTORC1 signaling, complement, and inflammatory response pathways mentioned.

Strengths

• Data integrates multi-omics sources including scRNA-seq, GWAS, and GTEx expression data.
• Analysis employed seven machine learning algorithms and a benchmark to select the best model.
• Includes a validation dataset from scRNA-seq performed on peripheral blood from MG patients and controls.

Limitations

• The dataset is very small at 9.1 KB, indicating limited scope.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Integrated data from GEO, GWAS catalog, and GTEx databases, plus original scRNA-seq validation data.

Collection Method

Multi-omics integration, TWAS analysis, and machine learning performed on the collected data.

Freshness

Last updated 2026-05-01 05:25:21; freshness should be verified.