RT Journal Article
SR Electronic
T1 AVADA Enables Automated Genetic Variant Curation Directly from the Full Text Literature
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 461269
DO 10.1101/461269
A1 Johannes Birgmeier
A1 Andrew P. Tierno
A1 Peter D. Stenson
A1 Cole A. Deisseroth
A1 Karthik A. Jagadeesh
A1 David N. Cooper
A1 Jonathan A. Bernstein
A1 Maximilian Haeussler
A1 Gill Bejerano
YR 2018
UL http://biorxiv.org/content/early/2018/11/04/461269.abstract
AB Purpose The primary literature on human genetic diseases includes descriptions of pathogenic variants that are essential for clinical diagnosis. Variant databases such as ClinVar and HGMD collect pathogenic variants by manual curation. We aimed to automatically construct a freely accessible database of pathogenic variants directly from full-text articles about genetic disease.Methods AVADA (Automatically curated VAriant DAtabase) is a novel machine learning tool that uses natural language processing to automatically identify pathogenic variants and genes in full text of primary literature and converts them to genomic coordinates for rapid downstream use.Results AVADA automatically curated almost 60% of pathogenic variants deposited in HGMD, a 4.4-fold improvement over the current state of the art in automated variant extraction. AVADA also contains more than 60,000 pathogenic variants that are in HGMD, but not in ClinVar. In a cohort of 245 diagnosed patients, AVADA correctly annotated 38 previously described diagnostic variants, compared to 43 using HGMD, 20 using ClinVar and only 13 (wholly subsumed by AVADA and ClinVar’s) using the best automated abstracts-only based approach.Conclusion AVADA is the first machine learning tool that automatically curates a variants database directly from full text literature. AVADA is available upon publication at http://bejerano.stanford.edu/AVADA.