Sammanfattning

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.
Originalspråkengelska
Titel på gästpublikationData Mining for Systems Biology : Methods and Protocols
RedaktörerHiroshi Mamitsuka
Antal sidor7
UtgivningsortNew York, NY
FörlagHumana press
Utgivningsdatum2018
Utgåva2
Sidor1-7
ISBN (tryckt)978-1-4939-8560-9
ISBN (elektroniskt)978-1-4939-8561-6
DOI
StatusPublicerad - 2018
MoE-publikationstypA3 Del av bok eller annan forskningsbok

Publikationsserier

NamnMethods in Molecular Biology
FörlagHumana Press
Volym1807
ISSN (tryckt)1064-3745
ISSN (elektroniskt)1940-6029

Vetenskapsgrenar

  • 112 Statistik
  • 1183 Växtbiologi, mikrobiologi, virologi

Citera det här

Mäklin, T., Corander, J., & Honkela, A. (2018). Identifying Bacterial Strains from Sequencing Data. I H. Mamitsuka (Red.), Data Mining for Systems Biology: Methods and Protocols (2 red., s. 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. redaktör / Hiroshi Mamitsuka. 2. red. New York, NY : Humana press, 2018. s. 1-7 (Methods in Molecular Biology).
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Mäklin, T, Corander, J & Honkela, A 2018, Identifying Bacterial Strains from Sequencing Data. i H Mamitsuka (red.), Data Mining for Systems Biology: Methods and Protocols. 2 uppl, Methods in Molecular Biology, vol. 1807, Humana press, New York, NY, s. 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. red. / Hiroshi Mamitsuka. 2. red. New York, NY : Humana press, 2018. s. 1-7 (Methods in Molecular Biology; Vol. 1807).

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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.

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