Artificial intelligence enables comprehensive genome interpretation and nomination of candidate diagnoses for rare genetic diseases.

Francisco M De La VegaShimul ChowdhuryBarry MooreErwin FriseJeanette McCarthyEdgar Javier HernandezTerence WongKiely JamesLucia GuidugliPankaj B AgrawalCasie A GenettiCatherine A BrownsteinAlan H BeggsBritt-Sabina LöscherAndre FrankeBraden BooneShawn E LevyKatrin ÕunapSander PajusaluMatt HuentelmanKeri RamseyMarcus NaymikVinodh NarayananNarayanan VeeraraghavanPaul BillingsMartin G ReeseMark YandellStephen F Kingsmore

Published in: Genome medicine (2021)

GEM enabled diagnostic interpretation inclusive of all variant types through automated nomination of a very short list of candidate genes and disorders for final review and reporting. In combination with deep phenotyping by CNLP, GEM enables substantial automation of genetic disease diagnosis, potentially decreasing cost and expediting case review.

Keyphrases

artificial intelligence
machine learning
deep learning
genome wide
big data
copy number
dna methylation
emergency department
adverse drug