Journal article 454 views
Bayesian identication of bacterial strains from sequencing data
Aravind Sankar,
Brandon Malone,
Sion Bayliss,
Ben Pascoe 
,
Guillaume Meric,
Matthew Hitchings,
Samuel Sheppard,
Edward Feil,
Jukka Corander,
Antti Honkela
,
Guillaume Meric,
Matthew Hitchings,
Samuel Sheppard,
Edward Feil,
Jukka Corander,
Antti Honkela
arXiv.org
Swansea University Author:
Ben Pascoe
Abstract
Rapidly assaying the diversity a bacterial species present in a population obtained from for instance a hospital patient or an environmental source has become possible after recent technological advances in DNA sequencing. For several applications it is important to accurately identify the presence...
| Published in: | arXiv.org |
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| Published: |
2015
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| Online Access: |
http://arxiv.org/abs/1511.06546 |
| URI: | https://cronfa.swan.ac.uk/Record/cronfa23991 |
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| Abstract: |
Rapidly assaying the diversity a bacterial species present in a population obtained from for instance a hospital patient or an environmental source has become possible after recent technological advances in DNA sequencing. For several applications it is important to accurately identify the presence and estimate relative abundances of the target organisms from short sequence reads obtained for a sample. This task is particularly challenging when the set of interest includes very closely related organisms, such as different strains of pathogenic bacteria, which can vary considerably in terms of virulence, resistance and spread. Using advanced Bayesian statistical modelling and computation techniques we introduce a novel method for bacterial identification that is shown to outperform the currently leading pipeline for this purpose. Our approach enables fast and accurate sequence based identification of bacterial strains while using only modest computational resources. Hence it provides a useful tool for a wide spectrum of applications, including rapid clinical diagnostics to distinguish among closely related strains causing nosocomial infections. The software implementation is made freely available as an open source package. |
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| College: |
Faculty of Medicine, Health and Life Sciences |