Functional annotation of non-coding sequence variants
By G. Ritchie, I. Dunham, Eleftheria Zeggini, Paul Flicek. Nature Methods, 2014
324 citations recorded by the source corpus.
Identifying functionally relevant variants against the background of ubiquitous genetic variation is a major challenge in human genetics. For variants in protein-coding regions, our understanding of the genetic code and splicing allows us to identify likely candidates, but interpreting variants outside genic regions is more difficult. Here we present genome-wide annotation of variants (GWAVA), a tool that supports prioritization of noncoding variants by integrating various genomic and epigenomic annotations.
Subfields: Genetics, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/119eb9f47e4c63cc93d89d85a4b39ddf413d3c7c
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In Genetics
In Molecular Biology
- Jasper Snoek
- David R. Kelley
- Johannes Rinn
- Anshul B Kundaje
- Howard Y. Chang
- Avanti Shrikumar
- David P. Bartel
- Igor Ulitsky
Citations in the corpus
- Basset: learning the regulatory code of the accessible genome with deep convolutional neural networks (2015, background): “first stages of a mechanistic hypothesis can now be assigned to variants that directly overlap these annotations (Ritchie et al. 2014; Kircher et al. 2014; Fu et al. 2014).”