Amplicon design algorithm for single cell targeted DNA sequencing using machine learning

High throughput single cell DNA targeted sequencing enables the detection of rare mutations in cells and the identification of subclones defined by co-occurrence of mutations. The big challenge with multiplex sequencing at the single cell level is the non-uniform amplification of targeted regions during PCR. This results in an inadequate coverage of mutations of interest in the panel and hence makes genotyping challenging. To address this challenge, a machine learning engine was developed to optimize amplicon design for uniform amplification by making reliable performance prediction.