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Neptune: A Bioinformatics Tool for Rapid Discovery of Genomic Variation in Bacterial Populations

Eric Marinier, Rahat Zaheer, Chrystal Berry, Kelly Weedmark, Michael Domaratzki, Philip Mabon, Natalie Knox, Aleisha Reimer, Morag Graham, Linda Chui, The Canadian Listeria Detection and Surveillance using Next Generation Genomics (LiDS-NG) Consortium, Gary Van Domselaar
doi: https://doi.org/10.1101/032227
Eric Marinier
1National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
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Rahat Zaheer
1National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
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Chrystal Berry
1National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
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Kelly Weedmark
1National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
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Michael Domaratzki
2Department of Computer Science, University of Manitoba, Winnipeg, MB, Canada
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Philip Mabon
1National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
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Natalie Knox
1National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
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Aleisha Reimer
1National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
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Morag Graham
1National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
3Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, MB, Canada
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Linda Chui
4Provincial Laboratory for Public Health, Edmonton, AB, Canada
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Gary Van Domselaar
1National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
3Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, MB, Canada
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  • For correspondence: gary.vandomselaar@canada.ca
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Abstract

The ready availability of vast amounts of genomic sequence data has created the need to rethink comparative genomics algorithms using “big data” approaches. Neptune is an efficient system for rapidly locating differentially abundant genomic content in bacterial populations using an exact k-mer matching strategy, while accommodating k-mer mismatches. Neptune’s loci discovery process identifies sequences that are sufficiently common to a group of target sequences and sufficiently absent from non-targets using probabilistic models. Neptune uses parallel computing to efficiently identify and extract these loci from draft genome assemblies without requiring multiple sequence alignments or other computationally expensive comparative sequence analyses. Tests on simulated and real data sets showed that Neptune rapidly identifies regions that are both sensitive and specific. We demonstrate that this system can identify trait-specific loci from different bacterial lineages. Neptune is broadly applicable for comparative bacterial analyses, yet will particularly benefit pathogenomic applications, owing to efficient and sensitive discovery of differentially abundant genomic loci.

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Posted November 30, 2016.
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Neptune: A Bioinformatics Tool for Rapid Discovery of Genomic Variation in Bacterial Populations
Eric Marinier, Rahat Zaheer, Chrystal Berry, Kelly Weedmark, Michael Domaratzki, Philip Mabon, Natalie Knox, Aleisha Reimer, Morag Graham, Linda Chui, The Canadian Listeria Detection and Surveillance using Next Generation Genomics (LiDS-NG) Consortium, Gary Van Domselaar
bioRxiv 032227; doi: https://doi.org/10.1101/032227
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Neptune: A Bioinformatics Tool for Rapid Discovery of Genomic Variation in Bacterial Populations
Eric Marinier, Rahat Zaheer, Chrystal Berry, Kelly Weedmark, Michael Domaratzki, Philip Mabon, Natalie Knox, Aleisha Reimer, Morag Graham, Linda Chui, The Canadian Listeria Detection and Surveillance using Next Generation Genomics (LiDS-NG) Consortium, Gary Van Domselaar
bioRxiv 032227; doi: https://doi.org/10.1101/032227

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