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Genomic Epidemiology with Mixed Samples

View ORCID ProfileTommi Mäklin, View ORCID ProfileTeemu Kallonen, View ORCID ProfileJarno Alanko, View ORCID ProfileØrjan Samuelsen, View ORCID ProfileKristin Hegstad, View ORCID ProfileVeli Mäkinen, View ORCID ProfileJukka Corander, View ORCID ProfileEva Heinz, View ORCID ProfileAntti Honkela
doi: https://doi.org/10.1101/2020.04.03.021501
Tommi Mäklin
1Helsinki Institute for Information Technology HIIT, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
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  • For correspondence: tommi.maklin@helsinki.fi antti.honkela@helsinki.fi
Teemu Kallonen
2Department of Biostatistics, University of Oslo, Oslo, Norway
3Wellcome Sanger Institute, Hinxton, Cambridgeshire, UK
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Jarno Alanko
4Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki, Helsinki, Finland
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Ørjan Samuelsen
5Norwegian National Advisory Unit on Detection of Antimicrobial Resistance, Department of Microbiology and Infection Control, University Hospital of North Norway, Tromsø, Norway
6Department of Pharmacy, UiT The Arctic University of Norway, Tromsø, Norway
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Kristin Hegstad
5Norwegian National Advisory Unit on Detection of Antimicrobial Resistance, Department of Microbiology and Infection Control, University Hospital of North Norway, Tromsø, Norway
7Research group for Host-Microbe Interactions, Department of Medical Biology, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
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Veli Mäkinen
4Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki, Helsinki, Finland
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Jukka Corander
1Helsinki Institute for Information Technology HIIT, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
2Department of Biostatistics, University of Oslo, Oslo, Norway
3Wellcome Sanger Institute, Hinxton, Cambridgeshire, UK
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Eva Heinz
8Liverpool School of Tropical Medicine, Liverpool, United Kingdom
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Antti Honkela
4Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki, Helsinki, Finland
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  • ORCID record for Antti Honkela
  • For correspondence: tommi.maklin@helsinki.fi antti.honkela@helsinki.fi
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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").

  • https://github.com/PROBIC/mGEMS

  • https://github.com/algbio/themisto

  • https://zenodo.org/record/3724112

  • https://zenodo.org/record/3724101

  • https://zenodo.org/record/3724135

  • https://zenodo.org/record/4738948

  • https://zenodo.org/record/4738983

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted May 11, 2021.
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Genomic Epidemiology with Mixed Samples
Tommi Mäklin, Teemu Kallonen, Jarno Alanko, Ørjan Samuelsen, Kristin Hegstad, Veli Mäkinen, Jukka Corander, Eva Heinz, Antti Honkela
bioRxiv 2020.04.03.021501; doi: https://doi.org/10.1101/2020.04.03.021501
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Genomic Epidemiology with Mixed Samples
Tommi Mäklin, Teemu Kallonen, Jarno Alanko, Ørjan Samuelsen, Kristin Hegstad, Veli Mäkinen, Jukka Corander, Eva Heinz, Antti Honkela
bioRxiv 2020.04.03.021501; doi: https://doi.org/10.1101/2020.04.03.021501

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