Integrative Multi-Omics Data on HLA-DPA1/DPB1 in Pediatric Asthma

19.8 KB of transcriptomic data from airway epithelium and peripheral blood mononuclear cells of pediatric asthma patients. The dataset, authored by Yuchen Wen and last updated in June 2026, was generated by analyzing bulk and single-cell RNA-seq data from public repositories GSE152004, GSE65204, and GSE254127. It focuses on identifying HLA-DPA1 and HLA-DPB1 as candidate key genes linked to macrophage immune-metabolic dysregulation.

Use Cases

• Validating diagnostic biomarkers for pediatric asthma based on HLA-DPA1/DPB1 expression levels.
• Analyzing immune cell communication networks based on the described MIF signaling axis.
• Investigating macrophage subpopulation heterogeneity based on metabolic and stress-related functions.
• Training machine learning models for gene prioritization based on the four algorithms (SVM-RFE, Boruta, LASSO, XGBoost) used in the source study.

Strengths

• Data is derived from multiple public RNA-seq datasets (GSE152004, GSE65204, GSE254127), suggesting multi-source validation.
• Analysis employed four distinct machine learning algorithms for candidate gene identification.
• Includes experimental validation from IL-13-treated bronchial epithelial cells and patient samples.

Limitations

• The dataset is very small at 19.8 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

figshare

Collection Method

Bulk and single-cell RNA-sequencing analysis of patient samples and cell lines.

Freshness

Last updated 2026-06-03 04:54:40; freshness should be verified.