Imperial College London

DrNicholasCroucher

Faculty of MedicineSchool of Public Health

Reader in Bacterial Genomics
 
 
 
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Contact

 

+44 (0)20 7594 3820n.croucher

 
 
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Location

 

1104Sir Michael Uren HubWhite City Campus

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Summary

 

Publications

Citation

BibTex format

@article{Lees:2019:10.1101/gr.241455.118,
author = {Lees, JA and Harris, SR and Tonkin-Hill, G and Gladstone, RA and Lo, SW and Weiser, JN and Corander, J and Bentley, SD and Croucher, NJ},
doi = {10.1101/gr.241455.118},
journal = {Genome Research},
pages = {304--316},
title = {Fast and flexible bacterial genomic epidemiology with PopPUNK},
url = {http://dx.doi.org/10.1101/gr.241455.118},
volume = {29},
year = {2019}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - The routine use of genomics for disease surveillance provides the opportunity for high-resolution bacterial epidemiology. Current whole-genome clustering and multilocus typing approaches do not fully exploit core and accessory genomic variation, and they cannot both automatically identify, and subsequently expand, clusters of significantly similar isolates in large data sets spanning entire species. Here, we describe PopPUNK (Population Partitioning Using Nucleotide K -mers), a software implementing scalable and expandable annotation- and alignment-free methods for population analysis and clustering. Variable-length k-mer comparisons are used to distinguish isolates' divergence in shared sequence and gene content, which we demonstrate to be accurate over multiple orders of magnitude using data from both simulations and genomic collections representing 10 taxonomically widespread species. Connections between closely related isolates of the same strain are robustly identified, despite interspecies variation in the pairwise distance distributions that reflects species' diverse evolutionary patterns. PopPUNK can process 103-104 genomes in a single batch, with minimal memory use and runtimes up to 200-fold faster than existing model-based methods. Clusters of strains remain consistent as new batches of genomes are added, which is achieved without needing to reanalyze all genomes de novo. This facilitates real-time surveillance with consistent cluster naming between studies and allows for outbreak detection using hundreds of genomes in minutes. Interactive visualization and online publication is streamlined through the automatic output of results to multiple platforms. PopPUNK has been designed as a flexible platform that addresses important issues with currently used whole-genome clustering and typing methods, and has potential uses across bacterial genetics and public health research.
AU - Lees,JA
AU - Harris,SR
AU - Tonkin-Hill,G
AU - Gladstone,RA
AU - Lo,SW
AU - Weiser,JN
AU - Corander,J
AU - Bentley,SD
AU - Croucher,NJ
DO - 10.1101/gr.241455.118
EP - 316
PY - 2019///
SN - 1088-9051
SP - 304
TI - Fast and flexible bacterial genomic epidemiology with PopPUNK
T2 - Genome Research
UR - http://dx.doi.org/10.1101/gr.241455.118
UR - https://www.ncbi.nlm.nih.gov/pubmed/30679308
UR - http://hdl.handle.net/10044/1/67448
VL - 29
ER -