%0 Journal Article
%T Automated Clinical Exome Reanalysis Reveals Novel Diagnoses
%A Addie I. Nesbitt
%A Ahmad N. Abou Tayoun
%A Alisha B. Wilkens
%A Avni B. Santani
%A Bryan L. Krock
%A Cara M. Skraban
%A Chao Wu
%A Elizabeth H. Denenberg
%A Elizabeth J. Bhoj
%A Elizabeth T. DeChene
%A Emma C. Bedoukian
%A Ian D. Krantz
%A Jennifer Tarpinian
%A Jill R. Murrell
%A Jorune Balciuniene
%A Kajia Cao
%A Kieran B. Pechter
%A Laura K. Conlin
%A Livija Medne
%A Mahdi Sarmady
%A Matthew A. Deardorff
%A Matthew C. Dulik
%A Minjie Luo
%A Qiaoning Guan
%A Samuel W. Baker
%A Xiaonan Zhao
%A Zhenming Yu
%J The Journal of Molecular Diagnostics
%D 2019
%R 10.1016/j.jmoldx.2018.07.008
%X Clinical exome sequencing (CES) has a reported diagnostic yield of 20% to 30% for
most clinical indications. The ongoing discovery of novel gene¨Cdisease and variant¨Cdisease
associations are expected to increase the diagnostic yield of CES. Performing systematic
reanalysis of previously nondiagnostic CES samples represents a significant challenge
for clinical laboratories. Here, we present the results of a novel automated reanalysis
methodology applied to 300 CES samples initially analyzed between June 2014 and September
2016.
%U https://jmd.amjpathol.org/article/S1525-1578(18)30062-X/fulltext