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.
Original languageEnglish
Title of host publicationData Mining for Systems Biology : Methods and Protocols
EditorsHiroshi Mamitsuka
Number of pages7
Place of PublicationNew York, NY
PublisherHumana press
Publication date2018
Edition2
Pages1-7
ISBN (Print)978-1-4939-8560-9
ISBN (Electronic)978-1-4939-8561-6
DOIs
Publication statusPublished - 2018
MoE publication typeA3 Book chapter

Publication series

NameMethods in Molecular Biology
PublisherHumana Press
Volume1807
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029

Fields of Science

  • 112 Statistics and probability
  • 1183 Plant biology, microbiology, virology

Cite this

Mäklin, T., Corander, J., & Honkela, A. (2018). Identifying Bacterial Strains from Sequencing Data. In H. Mamitsuka (Ed.), Data Mining for Systems Biology: Methods and Protocols (2 ed., pp. 1-7). (Methods in Molecular Biology; Vol. 1807). New York, NY: Humana press. https://doi.org/10.1007/978-1-4939-8561-6_1
Mäklin, Tommi ; Corander, Jukka ; Honkela, Antti . / Identifying Bacterial Strains from Sequencing Data. Data Mining for Systems Biology: Methods and Protocols. editor / Hiroshi Mamitsuka. 2. ed. New York, NY : Humana press, 2018. pp. 1-7 (Methods in Molecular Biology).
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Mäklin, T, Corander, J & Honkela, A 2018, Identifying Bacterial Strains from Sequencing Data. in H Mamitsuka (ed.), Data Mining for Systems Biology: Methods and Protocols. 2 edn, Methods in Molecular Biology, vol. 1807, Humana press, New York, NY, pp. 1-7. https://doi.org/10.1007/978-1-4939-8561-6_1

Identifying Bacterial Strains from Sequencing Data. / Mäklin, Tommi; Corander, Jukka ; Honkela, Antti .

Data Mining for Systems Biology: Methods and Protocols. ed. / Hiroshi Mamitsuka. 2. ed. New York, NY : Humana press, 2018. p. 1-7 (Methods in Molecular Biology; Vol. 1807).

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

TY - CHAP

T1 - Identifying Bacterial Strains from Sequencing Data

AU - Mäklin, Tommi

AU - Corander, Jukka

AU - Honkela, Antti

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

KW - 112 Statistics and probability

KW - 1183 Plant biology, microbiology, virology

U2 - 10.1007/978-1-4939-8561-6_1

DO - 10.1007/978-1-4939-8561-6_1

M3 - Chapter

SN - 978-1-4939-8560-9

T3 - Methods in Molecular Biology

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EP - 7

BT - Data Mining for Systems Biology

A2 - Mamitsuka, Hiroshi

PB - Humana press

CY - New York, NY

ER -

Mäklin T, Corander J, Honkela A. Identifying Bacterial Strains from Sequencing Data. In Mamitsuka H, editor, Data Mining for Systems Biology: Methods and Protocols. 2 ed. New York, NY: Humana press. 2018. p. 1-7. (Methods in Molecular Biology). https://doi.org/10.1007/978-1-4939-8561-6_1