PT  - JOURNAL ARTICLE
AU  - Tommi Mäklin
AU  - Teemu Kallonen
AU  - Jarno Alanko
AU  - Ørjan Samuelsen
AU  - Kristin Hegstad
AU  - Veli Mäkinen
AU  - Jukka Corander
AU  - Eva Heinz
AU  - Antti Honkela
TI  - Genomic Epidemiology with Mixed Samples
AID  - 10.1101/2020.04.03.021501
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2020.04.03.021501
4099  - http://biorxiv.org/content/early/2021/05/11/2020.04.03.021501.short
4100  - http://biorxiv.org/content/early/2021/05/11/2020.04.03.021501.full
AB  - 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.