Yongbin Wang published results of consensus clustering analysis on figshare in April 2026. The 10.7 KB XLSX file contains candidate biomarkers for idiopathic pulmonary fibrosis identified through multi-omics integration and machine learning. The analysis integrated bulk and single-cell transcriptomic data with literature-derived gene sets.
Use Cases
- Validating candidate biomarkers CD247, IL7R, and RETN based on the multi-omics analysis described.
- Training diagnostic models for idiopathic pulmonary fibrosis based on the identified feature genes.
- Analyzing mitochondrial dynamics-associated pathways in fibrotic diseases based on the enrichment results.
- Investigating cell-type-specific expression patterns in monocyte-associated compartments based on the single-cell analysis mentioned.
Strengths
- Dataset is openly licensed under CC-BY-4.0.
- Analysis integrated multiple data types, including bulk transcriptomics, single-cell RNA-seq, and literature-derived gene sets.
- Candidate biomarkers were validated in an independent clinical cohort using RT-qPCR.
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 10.7 KB, indicating limited raw data scope.
Provenance
- Source
- figshare, author Yongbin Wang.
- Collection Method
- Integrated analysis of public Gene Expression Omnibus (GEO) datasets and single-cell RNA sequencing data.
- Time Range
- null
- Freshness
- Last updated 2026-04-23 17:24:13; freshness should be verified.
- Geography
- null