Multi-Omics Analysis of Inflammation in Acute Mountain Sickness

An integrative multi-omics analysis of acute mountain sickness (AMS) and high-altitude cerebral edema (HACE) from figshare. The dataset includes results from bulk RNA-seq, non-coding RNA-seq, and single-cell RNA-seq analyses, identifying 323 differentially expressed genes and inflammation-related molecular networks. It was authored by Zhicheng Xiang and last updated on 2026-05-22.

Use Cases

• Identify key inflammation-related genes and pathways in AMS based on the 323 differentially expressed genes.
• Construct regulatory networks based on the described protein-protein, miRNA-mRNA, transcription factor, and drug-gene interactions.
• Analyze cell-type-specific expression patterns based on the single-cell and deconvolution analyses highlighting monocytes.
• Validate potential therapeutic targets based on the identification of HBEGF as a key gene from drug-gene analysis.

Strengths

• Integrates multiple omics data types (bulk RNA-seq, non-coding RNA-seq, single-cell RNA-seq) for a multi-faceted analysis.
• Identifies a specific set of 323 differentially expressed genes, including 5 inflammation-related genes.
• Includes experimental validation from a hypobaric hypoxia-induced HACE mouse model.

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 (8.4 KB), suggesting it contains summary results rather than raw sequencing data.

Provenance

Source

figshare, author Zhicheng Xiang.

Collection Method

Integrative analysis of public RNA-seq datasets (GSE75665, GSE90500) and single-cell RNA-seq data, combined with experimental validation in a mouse model.

Freshness

Last updated 2026-05-22 11:13:43; freshness should be verified.