Biological relevance of computationally predicted pathogenicity of noncoding variants
Researchers can make use of a variety of computational tools to prioritize genetic variants and predict their pathogenicity. Here, the authors evaluate the performance of six of these tools in three typical biological tasks and find generally low concordance of predictions and experimental confirmat...
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2019
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oai:doaj.org-article:8f40bef121824d3e8e8c9116ae4aae2d2021-12-02T14:35:30ZBiological relevance of computationally predicted pathogenicity of noncoding variants10.1038/s41467-018-08270-y2041-1723https://doaj.org/article/8f40bef121824d3e8e8c9116ae4aae2d2019-01-01T00:00:00Zhttps://doi.org/10.1038/s41467-018-08270-yhttps://doaj.org/toc/2041-1723Researchers can make use of a variety of computational tools to prioritize genetic variants and predict their pathogenicity. Here, the authors evaluate the performance of six of these tools in three typical biological tasks and find generally low concordance of predictions and experimental confirmation.Li LiuMaxwell D. SanderfordRavi PatelPramod ChandrashekarGreg GibsonSudhir KumarNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-11 (2019) |
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Science Q Li Liu Maxwell D. Sanderford Ravi Patel Pramod Chandrashekar Greg Gibson Sudhir Kumar Biological relevance of computationally predicted pathogenicity of noncoding variants |
description |
Researchers can make use of a variety of computational tools to prioritize genetic variants and predict their pathogenicity. Here, the authors evaluate the performance of six of these tools in three typical biological tasks and find generally low concordance of predictions and experimental confirmation. |
format |
article |
author |
Li Liu Maxwell D. Sanderford Ravi Patel Pramod Chandrashekar Greg Gibson Sudhir Kumar |
author_facet |
Li Liu Maxwell D. Sanderford Ravi Patel Pramod Chandrashekar Greg Gibson Sudhir Kumar |
author_sort |
Li Liu |
title |
Biological relevance of computationally predicted pathogenicity of noncoding variants |
title_short |
Biological relevance of computationally predicted pathogenicity of noncoding variants |
title_full |
Biological relevance of computationally predicted pathogenicity of noncoding variants |
title_fullStr |
Biological relevance of computationally predicted pathogenicity of noncoding variants |
title_full_unstemmed |
Biological relevance of computationally predicted pathogenicity of noncoding variants |
title_sort |
biological relevance of computationally predicted pathogenicity of noncoding variants |
publisher |
Nature Portfolio |
publishDate |
2019 |
url |
https://doaj.org/article/8f40bef121824d3e8e8c9116ae4aae2d |
work_keys_str_mv |
AT liliu biologicalrelevanceofcomputationallypredictedpathogenicityofnoncodingvariants AT maxwelldsanderford biologicalrelevanceofcomputationallypredictedpathogenicityofnoncodingvariants AT ravipatel biologicalrelevanceofcomputationallypredictedpathogenicityofnoncodingvariants AT pramodchandrashekar biologicalrelevanceofcomputationallypredictedpathogenicityofnoncodingvariants AT greggibson biologicalrelevanceofcomputationallypredictedpathogenicityofnoncodingvariants AT sudhirkumar biologicalrelevanceofcomputationallypredictedpathogenicityofnoncodingvariants |
_version_ |
1718391143508475904 |