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.
