Running spell-check to identify regulatory variants
Martin Kircher1, Jay Shendure1
1Department of Genome Sciences, University of Washington, Seattle, Washington, USA.
Abstract:
A major challenge in human genetics is pinpointing which non-coding genetic variants affect gene expression and disease risk. A new study in this issue describes a broadly applicable approach for this task that explicitly models cell type-specific regulatory motifs and generates variant effect predictions that are more accurate and interpretable than those of alternative tools.
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