A machine-compiled database of genome-wide association studies.

Kuleshov, Volodymyr; Ding, Jialin; Vo, Christopher; Hancock, Braden; Ratner, Alexander; Li, Yang; Ré, Christopher; Batzoglou, Serafim et al. · Nat Commun · 2019

basic_science · Level V

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Abstract

Tens of thousands of genotype-phenotype associations have been discovered to date, yet not all of them are easily accessible to scientists. Here, we describe GWASkb, a machine-compiled knowledge base of genetic associations collected from the scientific literature using automated information extraction algorithms. Our information extraction system helps curators by automatically collecting over 6,000 associations from open-access publications with an estimated recall of 60-80% and with an estimated precision of 78-94% (measured relative to existing manually curated knowledge bases). This system represents a fully automated GWAS curation effort and is made possible by a paradigm for constructing machine learning systems called data programming. Our work represents a step towards making the curation of scientific literature more efficient using automated systems.

Medical subject headings