ICSNPathway

ICSNPathway identifies candidate causal single nucleotide polymorphisms (SNPs) and their associated biological pathways from genome-wide association study (GWAS) data.

Key Features:

• Linkage Disequilibrium (LD) Analysis: Assesses the non-random association of alleles at different loci to prioritize candidate causal SNPs from significant GWAS findings.
• Functional SNP Annotation: Annotates SNPs with functional information to infer potential impacts on biological processes or disease mechanisms.
• Pathway-Based Analysis (PBA): Identifies candidate causal pathways linked to the most significant SNPs to interpret pathway-level effects of genetic variation.
• SNP→Gene→Pathway Mapping: Maps SNPs to genes and subsequently to pathways to generate mechanistic hypotheses linking variants to biological processes.
• Integration of Analyses: Synthesizes LD analysis, functional annotation, and PBA to prioritize causal SNPs and their associated pathways.

Scientific Applications:

• GWAS interpretation: Prioritizes candidate causal SNPs from GWAS results to facilitate biological interpretation of association signals.
• Elucidation of disease mechanisms: Links SNPs to pathways to clarify biological mechanisms underlying complex traits and diseases.
• Hypothesis generation: Produces SNP→gene→pathway hypotheses for downstream functional validation and disease mechanism studies.
• Target identification: Highlights pathway-level perturbations associated with GWAS signals to support identification of potential therapeutic targets.

Methodology:

Performs linkage disequilibrium (LD) analysis, functional SNP annotation, and pathway-based analysis (PBA), and synthesizes these results to map SNPs to genes and pathways.