A 13.6 MB Excel file contains results from a multi-omics study investigating the gut-immune-lung axis in idiopathic pulmonary fibrosis. The dataset likely includes integrated analyses from bulk RNA-seq, single-cell profiles, spatial transcriptomics, and experimental validation. It was authored by Zhengyu Hu and last updated on March 19, 2026.
Use Cases
- Validate core IPF gene signatures (CXCL13, IL33, TLR4, IGF1) based on the multi-omics integration described.
- Develop machine learning models for IPF diagnosis based on the four-gene model mentioned.
- Investigate causal relationships between gut microbiota and IPF risk based on the Mendelian randomization analysis.
- Identify potential drug candidates for IPF based on the drug-signature reversal analysis.
- Study fibroblast-immune crosstalk in fibrotic foci based on the spatial mapping and deconvolution results.
Strengths
- Integrates multiple data types: bulk RNA-seq, single-cell, spatial transcriptomics, and blood multi-omics.
- Includes experimental validation from qPCR and ELISA assays in vitro, in vivo, and in patient plasma.
- Results are supported by machine learning techniques and causal inference via Mendelian randomization.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- The dataset is 13.6 MB, which suggests a relatively small scale for multi-omics data.
Provenance
- Source
- figshare
- Collection Method
- In silico integration of publicly available datasets and experimental validation.
- Freshness
- Last updated 2026-03-19 05:17:44; freshness should be verified.