SNPsea

SNPsea identifies cell types, tissues, and pathways enriched for trait-associated single-nucleotide polymorphism (SNP) loci to interpret genetic risk.

Key Features:

• Enrichment Analysis: Tests trait-associated genomic loci for enrichment in specific cell types, tissues, and pathways.
• Non-Parametric Statistical Approach: Computes empirical P-values by comparing observed SNP sets against null SNP sets/distributions using a non-parametric method.
• C++ Implementation: Implements the SNP set enrichment algorithm in C++ for fast and robust execution.
• General Applicability: Applies across various genomic datasets and traits as a general-purpose SNP set enrichment algorithm.

Scientific Applications:

• Red Blood Cell Count: Identifies cell types and pathways that may influence red blood cell production or regulation.
• Multiple Sclerosis: Explores genetic risk loci to uncover affected biological processes relevant to disease mechanisms.
• Celiac Disease: Investigates tissue-specific effects of SNPs to better understand the pathogenesis of this autoimmune disorder.
• HDL Cholesterol: Analyzes pathways that may be impacted by genetic variations influencing HDL cholesterol levels.

Methodology:

Evaluates trait-associated genomic loci for specificity to cell types, tissues, and pathways using a SNP set enrichment algorithm and computes empirical P-values via non-parametric comparisons with null SNP sets.