Functionally derived variant dataset

Published on 2017-03-01T00:33:46Z (GMT) by KHALID MAHMOOD
<div>Here we provide genetic variant data mined from large scale biochemical assays of protein function. These dataset will serve as a valuable resource for assessing performance of variant effect prediction methods.</div><div><br></div><div>The dataset are:</div><div><br></div><div>UniFun - derived from UniProt mutagenesis data</div><div>BRCA1-DMS - derived from the deep mutational scanning (DMS) protocol applied to BRCA1</div><div>TP53-TA - TP53 transactivation assay (Kato et al. 2003).</div><div><br></div><div>Here we make available the variants in VCF format.</div><div><br></div><div>Please cite: </div><div><br></div><div>Khalid Mahmood, Chol-hee Jung, Gayle Philip, Peter Georgeson, Jessica Chung, Bernard J. Pope and Daniel J. Park*, Variant effect prediction tools assessed using independent, functional assay-based datasets: implications for discovery and diagnostics.</div>

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MAHMOOD, KHALID (2017): Functionally derived variant dataset. University of Melbourne.

https://doi.org/10.4225/49/58b616ec5651c

Retrieved: 06:16, Nov 18, 2017 (GMT)

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