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      pyseer: a comprehensive tool for microbial pangenome-wide association studies

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          Abstract

          Summary

          Genome-wide association studies (GWAS) in microbes have different challenges to GWAS in eukaryotes. These have been addressed by a number of different methods. pyseer brings these techniques together in one package tailored to microbial GWAS, allows greater flexibility of the input data used, and adds new methods to interpret the association results.

          Availability and implementation

          pyseer is written in python and is freely available at https://github.com/mgalardini/pyseer, or can be installed through pip. Documentation and a tutorial are available at http://pyseer.readthedocs.io.

          Supplementary information

          Supplementary data are available at Bioinformatics online.

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          Most cited references2

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          Phandango: an interactive viewer for bacterial population genomics

          J Hadfield (2018)
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            Mash: fast genome and metagenome distance estimation using MinHash

            B.D. Ondov (2017)
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              Author and article information

              Contributors
              Role: Associate Editor
              Journal
              Bioinformatics
              Bioinformatics
              bioinformatics
              Bioinformatics
              Oxford University Press
              1367-4803
              1367-4811
              15 December 2018
              02 July 2018
              02 July 2018
              : 34
              : 24
              : 4310-4312
              Affiliations
              [1 ]Department of Microbiology, New York University School of Medicine, New York, NY, USA
              [2 ]European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
              [3 ]Department of Parasites and Microbes, Wellcome Sanger Institute, Hinxton, UK
              [4 ]Department of Biostatistics, University of Oslo, Oslo, Norway
              [5 ]Helsinki Institute of Information Technology (HIIT), Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
              Author notes

              The authors wish it to be known that, in their opinion, the John A. Lees and Marco Galardini authors should be regarded as Joint First Authors.

              To whom correspondence should be addressed. E-mail: john.lees@ 123456nyumc.org or marco@ 123456ebi.ac.uk
              Author information
              http://orcid.org/0000-0001-5360-1254
              http://orcid.org/0000-0001-7168-8090
              Article
              bty539
              10.1093/bioinformatics/bty539
              6289128
              30535304
              9bdad200-93a9-44f9-8f97-47c0f67dde31
              © The Author(s) 2018. Published by Oxford University Press.

              This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

              History
              : 16 February 2018
              : 27 May 2018
              : 27 June 2018
              Page count
              Pages: 3
              Funding
              Funded by: United States Public Health Service 10.13039/100007197
              Award ID: AI038446
              Award ID: AI105168
              Funded by: ERC 10.13039/100010663
              Award ID: 742158
              Funded by: SDB 10.13039/100009988
              Funded by: Wellcome 10.13039/100004440
              Award ID: 098051
              Categories
              Applications Notes
              Genetics and Population Analysis

              Bioinformatics & Computational biology
              Bioinformatics & Computational biology

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