Table 2_Single cell transcriptome signatures and cell-cell interactions associated with sa

Single-cell RNA-seq data from 16 sarcoidosis cases and 14 healthy controls, analyzed to characterize cellular composition, gene expression, and cell-cell communication. The dataset was created by Camille M. Moore and last updated on 2026-05-26. It includes findings on differential gene expression in macrophage and T cell populations and disruptions in cell signaling pathways.

Use Cases

• Identify disease-associated gene expression patterns based on differential expression analysis in macrophage subsets.
• Analyze shifts in immune cell communication networks based on cell-cell interaction data from CellChat.
• Investigate transcriptional alterations linked to disease progression based on comparisons between progressive and non-progressive sarcoidosis cases.
• Study pathway dysregulation in specific immune cell types based on upstream regulator analysis from Ingenuity Pathway Analysis.

Strengths

• Includes data from 30 total samples (16 sarcoidosis cases and 14 controls), providing a basis for comparative analysis.
• Analysis covers multiple immune cell types, including resident macrophages, recruited macrophages, and T cells, as described.
• Dataset is openly available under a CC-BY-4.0 license, facilitating reuse.

Limitations

• Row count and column-level documentation are unknown, which may limit suitability assessment.
• The dataset is small (33.6 KB), indicating limited scope, likely containing summary results rather than raw sequencing data.
• Description metadata is limited; actual data quality and structure require manual inspection after download.

Provenance

Source

figshare, author Camille M. Moore.

Collection Method

Single-cell RNA sequencing of bronchoalveolar lavage cells, analyzed with pseudobulk differential expression, Ingenuity Pathway Analysis, and CellChat.

Freshness

Last updated 2026-05-26 04:40:50; freshness should be verified.