Table 5_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, created by Camille M. Moore and last updated in May 2026, contains results from differential expression, pathway, and ligand-receptor interaction analyses. It is a small dataset at 22.3 KB, stored in an XLSX file.

Use Cases

• Identify disease-associated gene expression patterns based on differential expression results for macrophage and T cell populations.
• Analyze disrupted cell-cell communication networks based on the described ligand-receptor interaction analysis using CellChat.
• Investigate pathways and upstream regulators involved in sarcoidosis based on the Ingenuity Pathway Analysis (IPA) results mentioned.
• Compare immune cell population dynamics between progressive and non-progressive sarcoidosis cases based on the study design.

Strengths

• Data is derived from single-cell RNA-seq of 30 total samples (16 cases, 14 controls), providing cell-type resolution.
• Analysis includes specific findings on gene expression (e.g., IL1R1, PSTPIP2, CCL4) and disrupted signaling pathways (e.g., LGALS9-CD45).
• Dataset is openly licensed under CC-BY-4.0, permitting reuse with attribution.

Limitations

• Row count is unknown, which may limit suitability assessment for large-scale analyses.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small (22.3 KB), suggesting it contains summary results rather than raw sequencing data.

Provenance

Source

figshare, authored by Camille M. Moore.

Collection Method

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

Freshness

Last updated 2026-05-26 04:40:49; freshness should be verified.