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Identifying Bacterial Strains from Sequencing Data

  • Tommi Mäklin
  • Jukka Corander
  • Antti HonkelaEmail author
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1807)

Abstract

Environmental and clinical settings can host a wide variety of both bacterial species and strains in a single colony but accurate identification of the organisms is difficult. We describe BIB, a probabilistic method for estimating the relative abundances of species or strains contained in mixed samples analyzed by short read high-throughput sequencing. By grouping closely related strains together in clusters, the BIB pipeline is capable of estimating the relative abundances of the clusters contained in a sequencing sample.

Key words

Bacteria Strain identification Abundance estimation Metagenomics Probabilistic modelling 

Notes

Acknowledgements

This work was supported by the Academy of Finland [259440 to A.H., 251170 to J.C.].

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Tommi Mäklin
    • 1
  • Jukka Corander
    • 2
    • 3
  • Antti Honkela
    • 4
    • 5
    Email author
  1. 1.Helsinki Institute for Information Technology HIIT, Department of Mathematics and StatisticsUniversity of HelsinkiHelsinkiFinland
  2. 2.Helsinki Institute for Information Technology HIIT, Department of Mathematics and StatisticsUniversity of HelsinkiHelsinkiFinland
  3. 3.Department of BiostatisticsUniversity of OsloOsloNorway
  4. 4.Helsinki Institute for Information Technology HIIT, Department of Mathematics and StatisticsUniversity of HelsinkiHelsinkiFinland
  5. 5.Department of Public HealthUniversity of HelsinkiHelsinkiFinland

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