P807: Investigating the use of SpliceAI in variant reanalysis of a cohort of fetuses with congenital brain abnormalities

Splice-altering variants have been proposed as an important potential class of variants to explain the “missing heritability” of cases where a genetic etiology is strongly suspected but not revealed by current analysis. With improvements in machine learning, the ability to identify and characterize splice site variants has improved remarkably. Specifically, one such model powered by artificial intelligence, SpliceAI, has substantially improved accuracy compared to prior models and has started to be incorporated into research and clinical bioinformatic pipelines.