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

A 3.6 KB CSV file containing data from a multi-level transcriptomic analysis of pediatric asthma. The dataset, authored by Yuchen Wen and last updated in June 2026, likely contains results identifying HLA-DPA1 and HLA-DPB1 as candidate key genes downregulated in pediatric asthma, correlating with macrophage immune-metabolic dysregulation.

Use Cases

• Validate candidate gene identification based on the consensus of four machine learning algorithms (SVM-RFE, Boruta, LASSO, XGBoost).
• Analyze immune-metabolic dysregulation based on the correlation between HLA-DPA1/DPB1 downregulation and attenuated antigen presentation.
• Investigate macrophage heterogeneity based on single-cell RNA-seq analysis of Macro2 subsets.
• Study intercellular communication based on the identified MIF signaling axis between epithelial cells and macrophages/dendritic cells.

Strengths

• Data is derived from multiple validation sources, including bulk RNA-seq (GSE152004, GSE65204), in vitro experiments, and single-cell RNA-seq (GSE254127).
• Candidate genes were identified using a consensus of four distinct machine learning algorithms.
• Dataset is published under a permissive CC-BY-4.0 license.

Limitations

• The dataset is very small (3.6 KB), suggesting it contains summary-level 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.

Provenance

Source

figshare

Collection Method

Integrated analysis of bulk and single-cell RNA-sequencing data, machine learning screening, and experimental validation.

Freshness

Last updated 2026-06-03 04:54:42; freshness should be verified.