atSNP Search: a web resource for statistically evaluating influence of human genetic variation on transcription factor binding

• Published in: Bioinformatics Vol. 35; no. 15; pp. 2657 - 2659
• Main Authors: Shin, Sunyoung, Hudson, Rebecca, Harrison, Christopher, Craven, Mark, Keleş, Sündüz
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01.08.2019
• Subjects: Applications Notes; Genetic Variation; Genome-Wide Association Study; Humans; Protein Binding; Software; Transcription Factors
• ISSN: 1367-4803; 1460-2059; 1367-4811
• DOI: 10.1093/bioinformatics/bty1010

Abstract Summary Understanding the regulatory roles of non-coding genetic variants has become a central goal for interpreting results of genome-wide association studies. The regulatory significance of the variants may be interrogated by assessing their influence on transcription factor binding. We have developed atSNP Search, a comprehensive web database for evaluating motif matches to the human genome with both reference and variant alleles and assessing the overall significance of the variant alterations on the motif matches. Convenient search features, comprehensive search outputs and a useful help menu are key components of atSNP Search. atSNP Search enables convenient interpretation of regulatory variants by statistical significance testing and composite logo plots, which are graphical representations of motif matches with the reference and variant alleles. Existing motif-based regulatory variant discovery tools only consider a limited pool of variants due to storage or other limitations. In contrast, atSNP Search users can test more than 37 billion variant-motif pairs with marginal significance in motif matches or match alteration. Computational evidence from atSNP Search, when combined with experimental validation, may help with the discovery of underlying disease mechanisms. Availability and implementation atSNP Search is freely available at http://atsnp.biostat.wisc.edu. Supplementary information Supplementary data are available at Bioinformatics online.