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Methods Mol Biol. 2018;1807:1-7. doi: 10.1007/978-1-4939-8561-6_1.

Identifying Bacterial Strains from Sequencing Data.

Author information

1
Helsinki Institute for Information Technology HIIT, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland.
2
Department of Biostatistics, University of Oslo, Oslo, Norway.
3
Helsinki Institute for Information Technology HIIT, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland. antti.honkela@helsinki.fi.
4
Department of Public Health, University of Helsinki, Helsinki, Finland. antti.honkela@helsinki.fi.

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.

KEYWORDS:

Abundance estimation; Bacteria; Metagenomics; Probabilistic modelling; Strain identification

PMID:
30030799
DOI:
10.1007/978-1-4939-8561-6_1
[Indexed for MEDLINE]

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