PlasmidHawk is a linear time pan-genome alignment-based pipeline to predict the lab-of-origin of unknown sequences. Compared to the previous deep learning method, PlasmidHawk has higher prediction accuracy. PlasmidHawk can successfully predict unknown sequences’ depositing labs 76% of the time and 85% of the time the correct lab is in the top 10 candidates. In addition, PlasmidHawk can precisely single out the signature sub-sequences that are responsible for the lab-of-origin detection. PlasmidHawk represents an explainable and accurate tool for lab-of-origin prediction of synthetic plasmid sequences.