Nov 4, 2018

AVADA Enables Automated Genetic Variant Curation Directly from the Full Text Literature

BioRxiv : the Preprint Server for Biology
Johannes BirgmeierGill Bejerano

Abstract

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 lear...Continue Reading

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Mentioned in this Paper

Genome
Genes
Pathogenic Organism
Genomic Stability
Genomics
Extraction
Literature
Description
Hereditary Diseases
Gene Mutant

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