atSNP implements the affinity test for large sets of SNP-motif interactions using the importance sampling algorithm. Users may identify SNPs that potentially may affect binding affinity of transcription factors. Given a set of SNPs and a library of motif position weight matrices (PWMs), atSNP provides two main functions for analyzing SNP effects: (i) the binding affinity score for each allele and each PWM and the p-values for allele-specific binding affinity scores (ii) the p-values for affinity score changes between the two alleles for each SNP. Compared to other bioinformatics tools that provide similar functionalities, atSNP is highly scalable.
The atSNP main functions are:
LoadMotifLibrary - Load position weight matrices
LoadSNPData - Load the SNP information and code the
genome sequences around the SNP locations
LoadFastaData - Load the SNP data from fasta files
ComputeMotifScore - Compute the scores for SNP effects on
ComputePValues - Compute p-values for affinity scores
Some helper functions are:
MatchSubsequence - Compute the matching subsequence
GetIUPACSequence - Get the IUPAC sequence of a motif
dtMotifMatch - Compute the augmented matching subsequence
on SNP and reference alleles
The composite logo plotting function is:
plotMotifMatch - Plot sequence logos of the position
weight matrix of the motif and sequences of its corresponding best matching
augmented subsequence on the reference and SNP allele
Chandler Zuo Sunyoung Shin email@example.com
Zuo, Chandler, Shin, Sunyoung, and Keles, Sunduz. (2015). atSNP: Transcription factor binding affinity testing for regulatory SNP detection. Bioinformatics 31 (20): 3353-5.
atSNP vignette for more information
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