Abstract
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 Statement
The authors have declared no competing interest.
Footnotes
Major revision of the manuscript contents including the addition of a wet-lab benchmark for the method (described under the subheadings "Overview of the experiments used in benchmarking mGEMS" and "Evaluation of mGEMS and mSWEEP on the in vitro benchmark data").
