publication . Article . Other literature type . 2017

Sasquatch: predicting the impact of regulatory SNPs on transcription factor binding from cell- and tissue-specific DNase footprints.

Name: Sasquatch: predicting the impact of regulatory SNPs on transcription factor binding from cell- and tissue-specific DNase footprints.
Keywords: Genetics(clinical), Genetics, Method

Simon J. McGowan; James Hughes; Jelena Telenius; Maria Suciu; Doug Higgs; Ron Schwessinger; Stephen Taylor;

Open Access

Published: 13 Sep 2017

Publisher: Cold Spring Harbor Laboratory

Country: United Kingdom

Summary
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Abstract

In the era of genome-wide association studies (GWAS) and personalized medicine, predicting the impact of single nucleotide polymorphisms (SNPs) in regulatory elements is an important goal. Current approaches to determine the potential of regulatory SNPs depend on inadequate knowledge of cell-specific DNA binding motifs. Here, we present Sasquatch, a new computational approach that uses DNase footprint data to estimate and visualize the effects of noncoding variants on transcription factor binding. Sasquatch performs a comprehensive k-mer-based analysis of DNase footprints to determine any k-mer's potential for protein binding in a specific cell type and how this...

doi: 10.1101/gr.220202.117

pmid: 28904015

pmc: PMC5630036

Subjects

free text keywords: Genetics(clinical), Genetics, Method, Single-nucleotide polymorphism, ENCODE, Biology, Genome, DNA binding site, Genome-wide association study, Genetic association, Transcription factor, Computational biology, Personalized medicine, business.industry, business

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