%0 Journal Article %A Tommi Mäklin %A Teemu Kallonen %A Jarno Alanko %A Ørjan Samuelsen %A Kristin Hegstad %A Veli Mäkinen %A Jukka Corander %A Eva Heinz %A Antti Honkela %T Genomic Epidemiology with Mixed Samples %D 2021 %R 10.1101/2020.04.03.021501 %J bioRxiv %P 2020.04.03.021501 %X Genomic epidemiology is a tool for tracing transmission of pathogens based on whole-genome sequencing. We introduce the mGEMS pipeline for genomic epidemiology with plate sweeps representing mixed samples of a target pathogen, skipping the colony pick step. The pipeline includes the novel mGEMS read binner for probabilistic assignments of sequencing reads, and the scalable pseudoaligner Themisto. We demonstrate the effectiveness of our approach using closely related samples in a nosocomial setting, obtaining results that are comparable to those based on colony picks. Our results lend firm support to more widespread consideration of genomic epidemiology with mixed infection samples.Competing Interest StatementThe authors have declared no competing interest. %U https://www.biorxiv.org/content/biorxiv/early/2021/05/11/2020.04.03.021501.full.pdf