4.8 Article

Bringing the Animal QTLdb and CorrDB into the future: meeting new challenges and providing updated services

期刊

NUCLEIC ACIDS RESEARCH
卷 50, 期 D1, 页码 D956-D961

出版社

OXFORD UNIV PRESS
DOI: 10.1093/nar/gkab1116

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资金

  1. United States Department of Agriculture (USDA), National Animal Genome Research Program, Bioinformatics Coordination Project [8, NRSP-8]
  2. USDA-AFRI [2016-67015-24767]

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The Animal QTLdb and CorrDB, as unique resources, have evolved over the years to provide researchers with continually updated data and new web tools. These databases host a vast amount of information on QTL, SNP associations, correlations, and heritability data for multiple livestock species, with standardized procedures and the ability to browse data based on linked ontology terms as recent highlights.
The Animal QTLdb (https://www.animalgenome.org/QTLdb) and CorrDB (https://www.animalgenome.org/CorrDB) are unique resources for livestock animal genetics and genomics research which have been used extensively by the international livestock genome research community. This is largely due to the active development of the databases over the years to keep up with the rapid advancement of genome sciences. The ongoing development has ensured that these databases provide researchers not only with continually updated data but also with new web tools to disseminate the data. Through our continued efforts, the databases have evolved from the original Pig QTLdb for cross-experiment QTL data comparisons to an Animal QTLdb hosting 220 401 QTL, SNP association and eQTL data linking phenotype to genotype for 2210 traits. In addition, there are 23 552 correlations for 866 traits and 4273 heritability data on 1069 traits in CorrDB. All these data were curated from 3157 publications that cover seven livestock species. Along with the continued data curation, new species, additional genome builds, and new functions and features have been built into the databases as well. Standardized procedures to support data mapping on multiple species/genome builds and the ability to browse data based on linked ontology terms are highlights of the recent developments.

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