Abstract
Targeted sequencing of multiplex PCR amplicons is commonplace in research laboratories and clinical diagnostics. There are numerous tools for the a priori optimization of primers and reactions, but no tools to detect specific problematic primers post hoc. We developed URAdime, a tool for analyzing primer sequences in sequencing data to identify dimers and super-amplicons. We show that it successfully detects these unwanted amplicons and accurately aSributes their generation to specific primers.