AMELIE accelerates Mendelian patient diagnosis directly from the primary literature

The diagnosis of Mendelian disorders requires labor-intensive literature research. Our software system AMELIE (Automatic MEndelian LIterature Evaluation) greatly automates this process. AMELIE parses hundreds of thousands of full text articles to find an underlying diagnosis to explain a patient9s phenotypes given the patient9s exome. AMELIE prioritizes patient candidate genes for their likelihood of causing the patient9s phenotypes. Diagnosis of singleton patients (without relatives9 exomes) is the most time-consuming scenario. AMELIE9s gene ranking method was tested on 215 singleton Mendelian patients with a clinical diagnosis. AMELIE ranked the causal gene among the top 2 in the majority (63%) of cases. Examining AMELIE9s top 10 genes, amounting to 8% of 124 candidate genes with rare functional variants per patient, results in diagnosis for 95% of cases. Strikingly, training only on gene pathogenicity knowledge from 2011 leads to identical performance compared to training on current data. An accompanying analysis web portal has launched at AMELIE.stanford.edu.