<b>Potential of gut microbiota metabolites in treating allergic rhinitis: integrated multi

Yuxi Lin's dataset contains 31 files of raw data and scripts supporting a 2026 research article on gut microbiota metabolites in allergic rhinitis. The 92.7 MB repository includes GWAS summary data, transcriptomic profiles from GEO datasets GSE261239 and GSE43523, and 3D structural data for molecular docking. It provides the complete analytical pipeline executed in R version 4.2.2.

Use Cases

• Reproducing Mendelian randomization analysis to identify causal gut microbiota on allergic rhinitis based on the provided GWAS summary data.
• Training machine learning models for feature selection of metabolic-immune sensors using the included transcriptomic profiles and R scripts for Boruta and Random Forest.
• Validating specific regulatory networks like Lachnoclostridium-5-3HPA-ALDH2 through molecular docking based on the supplied 3D structural data.
• Conducting functional enrichment analysis on prioritized host genes using the provided R packages like clusterProfiler.

Strengths

• Includes 31 files providing a complete analytical pipeline for reproducibility.
• Contains specific, validated regulatory network axes (e.g., Lachnoclostridium-5-3HPA-ALDH2) as described in the research.
• Integrates data from multiple sources, including GWAS summary statistics and two GEO transcriptomic datasets (GSE261239, GSE43523).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for certain analyses.
• Data may reflect bias inherent to the specific GWAS and GEO sources used.

Provenance

Source

Yuxi Lin, via figshare.

Collection Method

Data compiled from GWAS summary statistics, GEO transcriptomic datasets, and generated through R-based computational analysis.

Freshness

Last updated 2026-04-22 13:18:09; freshness should be verified.