SNPhood

SNPhood analyzes local genomic neighborhoods of single nucleotide polymorphisms to quantify and visualize epigenetic signals (chromatin marks and transcription factor binding) from NGS experiments such as ChIP-Seq and RNA-Seq.

Key Features:

• Integration with NGS data: Processes NGS datasets including ChIP-Seq and RNA-Seq to associate chromatin marks and transcription factor binding with SNP loci.
• Regulatory element focus: Profiles SNPs in non-coding regulatory elements including enhancers and promoters to assess potential regulatory impacts.
• Read extraction, normalization, and summarization: Extracts, normalizes, and summarizes sequencing reads across genomic windows surrounding SNPs to produce quantitative measures of epigenetic signals.
• Visualization: Generates graphical representations of chromatin marks and transcription factor binding across SNP-centered regions.

Scientific Applications:

• Regulatory effect interpretation: Interpreting how disease-associated SNPs in non-coding regions affect gene expression and chromatin structure.
• Molecular mechanism discovery: Linking SNPs to nearby molecular traits to provide insights into the molecular mechanisms underlying genetic diseases.
• Functional follow-up prioritization: Supporting detailed analysis of SNP-associated epigenetic modifications to inform selection of candidate regulatory mechanisms, therapeutic targets, or biomarkers.

Methodology:

SNPhood extracts and normalizes NGS reads from genomic regions surrounding SNPs and summarizes these data to quantify chromatin marks and transcription factor binding.