Table 10_Exploration of candidate genes associated with rare SNVs in pulmonary stenosis us

185 sporadic pulmonary stenosis patients and 100 healthy controls were analyzed using whole-exome sequencing and multiple machine learning algorithms. The dataset contains results prioritizing 17 candidate genes associated with the condition, published by Yuting Liu in June 2026. It is shared under a CC-BY-4.0 license on figshare as a 663.5 KB Excel file.

Use Cases

• Prioritizing candidate disease genes based on rare variant burden test results
• Comparing feature selection patterns across LASSO, Random Forest, and XGBoost algorithms
• Validating candidate genes through protein-protein interaction network analysis
• Cross-referencing prioritized genes with expression data from human pulmonary artery endothelial cells

Strengths

• Data is derived from whole-exome sequencing of 185 patients and 100 controls, providing a case-control study foundation
• Results include 17 specific candidate genes prioritized through multiple analytical methods
• The dataset is openly shared under a permissive CC-BY-4.0 license

Limitations

• The dataset is small in scale at 663.5 KB, indicating limited raw data or summary-level results
• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment for large-scale modeling

Provenance

Source

figshare

Collection Method

Whole-exome sequencing data analyzed with pathogenicity-filtering strategies, gene-level burden tests, and machine learning algorithms.

Freshness

Last updated 2026-06-04 22:01:41; freshness should be verified