Mouse Osteomyelitis Immune Cell Gene Expression from Single-Cell and Bulk RNA-seq

Transcriptomic data from mouse osteomyelitis samples in dataset GSE168896, analyzed for immune cell infiltration and gene expression dynamics. The dataset includes results from fuzzy c-means clustering and single-cell sequencing, identifying six gene clusters and seven cellular subpopulations. It was authored by Zhenhua Zhu and last updated on 2026-03-18.

Use Cases

• Identify temporal gene expression patterns in osteomyelitis based on the six described gene clusters.
• Characterize immune cell subpopulations based on the seven distinct cell types identified via single-cell sequencing.
• Investigate macrophage infiltration dynamics based on the reported increase in specific macrophage subtypes (Mif+Cd63+, Arg1+Sdc4+, Cxcl1+Ccl4+).
• Analyze ligand-receptor interactions in immune cells based on the highlighted Ccl3–Ccr1 and Cxcl2–Cxcr2 signaling pathways.

Strengths

• Data integrates both single-cell and bulk RNA-seq analysis for a multi-faceted view.
• Analysis identified six specific gene clusters with distinct temporal expression patterns.
• Single-cell sequencing resolved seven distinct cellular subpopulations.
• Specific macrophage subtypes and signaling pathways are highlighted as key findings.

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 small (33.4 KB), indicating limited scope, likely containing summary results rather than raw sequencing data.

Provenance

Source

figshare, author Zhenhua Zhu.

Collection Method

Analysis of time-series transcriptomic sequencing data from mouse osteomyelitis samples in the dataset GSE168896, using fuzzy c-means clustering, ImmuCellAI-mouse, and single-cell sequencing.

Freshness

Last updated 2026-03-18 07:37:10; freshness should be verified.