Table 7_Single cell transcriptome signatures and cell-cell interactions associated with sa

Single-cell RNA sequencing data from bronchoalveolar lavage cells of 16 sarcoidosis patients and 14 healthy controls, analyzed by Camille M. Moore. The dataset captures gene expression patterns and cell-cell communication networks associated with pulmonary sarcoidosis and its progression. It was last updated on 2026-05-26.

Use Cases

• Identify disease-associated gene expression changes based on differential expression analysis of macrophage and T cell populations.
• Investigate disrupted immune signaling pathways based on upstream regulator analysis of TNF, IFNG, and IL1B in CD4+ T cells.
• Analyze shifts in cell-cell communication networks based on the reported reduction in overall interactions and specific downregulation of LGALS9-CD45 signaling.
• Compare immune cell composition between disease states based on the reported significant reduction in B cell numbers in sarcoidosis.

Strengths

• Data includes 30 total samples (16 cases, 14 controls) with clinical stratification into 8 progressive and 8 non-progressive sarcoidosis cases.
• Analysis includes multiple layers: differential gene expression, pathway analysis, and cell-cell interaction mapping using CellChat.
• Dataset is openly available under a CC-BY-4.0 license.

Limitations

• The dataset is small at 36.2 KB, suggesting it contains summary-level results rather than raw sequencing data.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for certain analyses.

Provenance

Source

figshare

Collection Method

Single-cell RNA-seq analysis of bronchoalveolar lavage cells, using pseudobulk differential expression and CellChat for interaction inference.

Freshness

Last updated 2026-05-26 04:40:48; freshness should be verified.