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Thesis

Efficient analysis of microbial whole-genome sequence data using de Bruijn graphs

Abstract:

Antimicrobial resistance (AMR) is a persistent and growing threat to global health. Whole genome sequencing (WGS) has the potential to dramatically improve our ability to detect, understand, and monitor AMR. However, microbial diversity and complexity means that the analysis and interpretation of their genomes is challenging. In this thesis, I explore applications of de Bruijn graphs (DBGs) to the analysis of these data.

First, I present a tool, Mykrobe predictor, that uses DBGs to ...

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Phelim Bradley More by this author

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Role:
Supervisor
Role:
Supervisor
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Grant:
H52017782
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Project
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford

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