A database of 453 primary immunodeficiency (PID) genes analyzed for their role in systemic lupus erythematosus (SLE). The dataset includes protein-protein interaction networks, differential expression analysis across multiple sample types, and machine learning classifier results for predicting SLE status and severity. It was authored by Haley Davis and last updated in March 2026.
Use Cases
- Identifying novel SLE risk genes based on overlap with known PID genes.
- Analyzing differential expression patterns of PID genes in specific immune cell subsets like T cells and monocytes.
- Training machine learning classifiers to predict SLE disease status using PID gene groupings.
- Mapping functional protein-protein interaction clusters to understand cellular pathways in lupus pathogenesis.
- Investigating associations between PID gene expression and measures of lupus disease activity.
Strengths
- Includes a defined set of 453 primary immunodeficiency genes.
- Machine learning classifiers achieved reported accuracies of 0.80 and 0.74 for specific classification tasks.
- Analysis covers multiple sample types, including whole blood and immune cell-specific samples.
- Released under a permissive CC-BY-4.0 license.
Limitations
- Row count and column-level documentation are unknown, limiting suitability assessment.
- The dataset is very small at 12.8 KB, suggesting limited scope or summary-level data.
- Description metadata is limited; actual data quality requires manual inspection after download.
Provenance
- Source
- figshare
- Collection Method
- Developed from a comprehensive database of PID genes, clustered into networks and compared to SLE risk loci, with expression analysis and machine learning applied.
- Time Range
- null
- Freshness
- Last updated 2026-03-18 10:09:47; freshness should be verified.
- Geography
- null