Analysis of machine learning algorithms as integrative tools for validation of next generation sequencing data.

Our results show that it is possible to integrate the diagnostic NGS validation workflow with a machine learning approach to reduce the number of Sanger confirmations of high- quality NGS calls, reducing the time and costs of diagnosis.