atSNP

atSNP evaluates the impact of single nucleotide polymorphisms (SNPs) on transcription factor (TF) binding affinities by testing motif-SNP interactions.

Key Features:

• Implementation: Provided as an R package for computational analysis of motif-SNP interactions.
• Large-scale analysis: Capable of processing extensive SNP sets, demonstrated on datasets with over 20,000 SNPs.
• Statistical testing: Uses an importance sampling algorithm to assess significance of affinity scores and SNP-driven changes in those scores.
• Background modeling: Employs a first-order Markov model to establish background nucleotide sequence probabilities.
• Output formats: Produces tabular results and composite logo plots representing SNP-motif interactions.
• Motif prioritization: Demonstrated ability to prioritize motifs associated with given SNP sets with high accuracy.

Scientific Applications:

• Genome-wide association studies (GWAS): Identification and prioritization of regulatory SNPs (rSNPs) within introns and intergenic regions based on TF binding changes.
• Regulatory variant interpretation: Pinpointing SNPs that alter gene regulation through changes in TF binding affinities.
• Disease mechanism research: Linking SNP-induced TF affinity changes to genetic regulation relevant to disease studies.

Methodology:

An importance sampling algorithm combined with a first-order Markov model for background nucleotide sequences is used to test significance of affinity scores and SNP-driven changes in those scores.