Ensembl variation resources
Author(s) -
Sarah Hunt,
William McLaren,
Laurent Gil,
Anja Thormann,
Helen Schuilenburg,
Dan Sheppard,
Andrew Parton,
Irina M. Armean,
Stephen J. Trevanion,
Paul Flicek,
Fiona Cunningham
Publication year - 2018
Publication title -
database
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.406
H-Index - 62
ISSN - 1758-0463
DOI - 10.1093/database/bay119
Subject(s) - ensembl , annotation , computer science , data science , variety (cybernetics) , variation (astronomy) , information retrieval , data integration , genome , genomics , data mining , biology , artificial intelligence , biochemistry , physics , gene , astrophysics
The major goal of sequencing humans and many other species is to understand the link between genomic variation, phenotype and disease. There are numerous valuable and well-established variation resources, but collating and making sense of non-homogeneous, often large-scale data sets from disparate sources remains a challenge. Without a systematic catalogue of these data and appropriate query and annotation tools, understanding the genome sequence of an individual and assessing their disease risk is impossible. In Ensembl, we substantially solve this problem: we develop methods to facilitate data integration and broad access; aggregate information in a consistent manner and make it available a variety of standard formats, both visually and programmatically; build analysis pipelines to compare variants to comprehensive genomic annotation sets; and make all tools and data publicly available.
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