HLA-DPA1/DPB1 Gene Expression in Pediatric Asthma from Multi-Omics Analysis

HLA-DPA1 and HLA-DPB1 were identified as key downregulated genes in pediatric asthma through consensus of four machine learning algorithms. The 12.6 KB Excel file contains results from a multi-level analysis integrating bulk RNA-seq, single-cell RNA-seq, and experimental validation data. Yuchen Wen authored this dataset, which was last updated on June 3, 2026.

Use Cases

• Validate diagnostic biomarkers for pediatric asthma based on the identified downregulation of HLA-DPA1/DPB1.
• Study immune-metabolic dysregulation in macrophages based on the single-cell RNA-seq analysis of the Macro2 subset.
• Investigate cell-cell communication networks in asthma based on the described MIF signaling axis between epithelial cells and macrophages.
• Benchmark machine learning algorithms for gene selection based on the application of SVM-RFE, Boruta, LASSO, and XGBoost.

Strengths

• Results are validated across multiple datasets, including an independent validation set (GSE65204).
• Analysis integrates multiple data types, including bulk RNA-seq, single-cell RNA-seq (GSE254127), and in vitro experimental validation.
• Candidate genes were identified by consensus of four distinct machine learning algorithms.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 12.6 KB, indicating it likely contains summary results rather than raw sequencing data.

Provenance

Source

figshare, authored by Yuchen Wen.

Collection Method

Integrated analysis of public RNA-sequencing datasets (e.g., GSE152004, GSE65204, GSE254127) and experimental validation.

Freshness

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