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InStrain enables population genomic analysis from metagenomic data and rigorous detection of identical microbial strains
Matthew R. Olm, Alexander Crits-Christoph, Keith Bouma-Gregson, Brian Firek, Michael J. Morowitz, Jillian F. Banfield
doi: https://doi.org/10.1101/2020.01.22.915579
Matthew R. Olm
1Department of Earth and Planetary Science, University of California, Berkeley, CA, USA
2Department of Plant and Microbial Biology, University of California, Berkeley, CA, USA
Alexander Crits-Christoph
2Department of Plant and Microbial Biology, University of California, Berkeley, CA, USA
Keith Bouma-Gregson
3Office of Information Management and Analysis, California State Water Resources Control Board, Sacramento, CA, USA
Brian Firek
4Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
Michael J. Morowitz
4Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
Jillian F. Banfield
1Department of Earth and Planetary Science, University of California, Berkeley, CA, USA
5Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA, USA
6Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
7Chan Zuckerberg Biohub, San Francisco, CA, USA.
Article usage
Posted January 23, 2020.
InStrain enables population genomic analysis from metagenomic data and rigorous detection of identical microbial strains
Matthew R. Olm, Alexander Crits-Christoph, Keith Bouma-Gregson, Brian Firek, Michael J. Morowitz, Jillian F. Banfield
bioRxiv 2020.01.22.915579; doi: https://doi.org/10.1101/2020.01.22.915579
InStrain enables population genomic analysis from metagenomic data and rigorous detection of identical microbial strains
Matthew R. Olm, Alexander Crits-Christoph, Keith Bouma-Gregson, Brian Firek, Michael J. Morowitz, Jillian F. Banfield
bioRxiv 2020.01.22.915579; doi: https://doi.org/10.1101/2020.01.22.915579
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