Functional Annotation of Putative Regulatory Elements at Cancer Susceptibility Loci

Abstract

Most cancer-associated genetic variants identified from genome-wide association studies (GWAS) do not obviously change protein structure, leading to the hypothesis that the associations are attributable to regulatory polymorphisms. Translating genetic associations into mechanistic insights can be facilitated by knowledge of the causal regulatory variant (or variants) responsible for the statistical signal. Experimental validation of candidate functional variants is onerous, making bioinformatic approaches necessary to prioritize candidates for laboratory analysis. Thus, a systematic approach for recognizing functional (and, therefore, likely causal) variants in noncoding regions is an important step toward interpreting cancer risk loci. This review provides a detailed introduction to current regulatory variant annotations, followed by an overview of how to leverage these resources to prioritize candidate functional polymorphisms in regulatory regions.

DOI: 10.4137/CIN.S13789

Extracted Key Phrases

6 Figures and Tables

0204060201520162017
Citations per Year

Citation Velocity: 6

Averaging 6 citations per year over the last 3 years.

Learn more about how we calculate this metric in our FAQ.

Cite this paper

@inproceedings{Rosse2014FunctionalAO, title={Functional Annotation of Putative Regulatory Elements at Cancer Susceptibility Loci}, author={Stephanie A. Rosse and Paul L. Auer and Christopher S. Carlson}, booktitle={Cancer informatics}, year={2014} }