MIXER: a Machine-learning method to detect genomic Imbalances exploiting X chromosome exome reads

Whole Exome Sequencing (WES) is rapidly becoming a first-tier test, thanks to declining costs and automatic clinical pipelines. However, while identification of small variants follows standardized workflows, there is no agreement on methods for detection of Copy Number Variants (CNVs). A plethora of WES-based CNV callers have been developed, each showing good performance towards only a limited range of CNV classes/sizes. As clinical CNVs extend from large rearrangements to single genes, more versatile approaches are needed to be of enhanced diagnostic use.