FunciSNP

FunciSNP identifies candidate functional single nucleotide polymorphisms (SNPs) by integrating genome-wide association study (GWAS) signals, 1000 Genomes Project variants, and chromatin/epigenomic datasets to prioritize surrogate SNPs in non-coding regulatory regions.

Key Features:

• Integration of diverse datasets: Combines GWAS, 1000 Genomes Project variant data, and chromatin/epigenomic feature datasets for joint analysis.
• Surrogate SNP prioritization: Prioritizes surrogate SNPs based on their association with non-coding chromatin and epigenomic features.
• Focus on non-coding regulatory regions: Targets SNPs located in non-coding regions, addressing the challenge of distinguishing functional regulatory variants from linked tagSNPs.
• Use of sequencing-derived features: Utilizes chromatin and epigenomic features identified using massively parallel sequencing techniques.

Scientific Applications:

• Functional SNP identification at GWAS loci: Identifies candidate functional variants within GWAS-associated loci by integrating genetic linkage and epigenomic context.
• Elucidation of disease and trait mechanisms: Prioritizes variants for studies probing the molecular mechanisms underlying complex diseases and phenotypic variation.

Methodology:

Implemented as an R/Bioconductor package that integrates GWAS, 1000 Genomes Project variant data, and chromatin/epigenomic feature datasets, and prioritizes surrogate SNPs based on their association with non-coding chromatin and epigenomic features derived from massively parallel sequencing.