Evaluating the performance of a clinical genome sequencing program for diagnosis of rare genetic disease, seen through the lens of craniosynostosis.

Andrew O M WilkieEduardo CalpenaYang PeiRebecca S ToozeHelen BrittainStephen R F TwiggDeirdre CilliersJenny E V MortonEmma McCannAstrid WeberLouise C WilsonAndrew G L DouglasRuth McGowanAnna NeedAndrew BondAna Lisa Taylor TavaresEllen R A Thomasnull nullSusan L HillZandra C DeansFreya Boardman-PrettyMark CaulfieldRichard H ScottAndrew O M Wilkie

Published in: Genetics in medicine : official journal of the American College of Medical Genetics (2021)

GS identified likely pathogenic/pathogenic variants in 29.8% of previously undiagnosed patients with craniosynostosis. This demonstrates the value of research analysis and the importance of continually improving algorithms to maximize the potential of clinical GS.

Keyphrases

machine learning
genome wide
quality improvement
single cell
gene expression
risk assessment
data analysis