Single-Cell and Bulk RNA Sequencing of Spinal Tuberculosis and Brucellar Spondylitis

Integrated transcriptomic data from Zongqiang Yang, last updated in 2026, analyzes 67,274 high-quality cells from infected spinal tissues. The dataset combines single-cell RNA sequencing from 6 patients and bulk RNA sequencing from 12 patients to compare the immune pathology of spinal tuberculosis and Brucella spondylitis.

Use Cases

• Compare T-cell subset architecture and functional states between two spinal infections based on single-cell clustering results.
• Identify shared osteoclast differentiation pathways from integrated bulk and single-cell transcriptomic signatures.
• Analyze divergent immune cell communication networks, such as the MHC-II-CD4 axis versus MHC-I-CD8 axis, described in the results.
• Reconstruct pseudotime trajectories to model T-cell exhaustion and effector-memory progression mentioned in the analysis.

Strengths

• Integrated analysis of 67,274 high-quality single cells from a defined cohort of patients.
• Combines two sequencing modalities: single-cell RNA-seq (6 samples) and bulk RNA-seq (12 samples).
• Clear methodological description includes trajectory reconstruction, regulon inference, and cell-cell communication analysis.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Sample sizes are relatively small (3 patients per group for scRNA-seq).

Provenance

Source

figshare, author Zongqiang Yang.

Collection Method

Single-cell and bulk RNA sequencing of infected nucleus pulposus tissues from patient cohorts.

Freshness

Last updated 2026-05-19 05:38:29; freshness should be verified.