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Sundararaman B, Shapiro K, Packham A, Camp LE, Meyer RS, Shapiro B, Green RE. Whole genome enrichment approach for genomic surveillance of Toxoplasma gondii. Food Microbiol 2024; 118:104403. [PMID: 38049278 DOI: 10.1016/j.fm.2023.104403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 09/26/2023] [Accepted: 10/15/2023] [Indexed: 12/06/2023]
Abstract
Pathogenic bacteria, viruses, fungi, and protozoa can cause food and waterborne diseases. Surveillance methods must therefore screen for these pathogens at various stages of water distribution and of food from production to consumption. Detection using nucleic acid amplification methods offer rapid identification, but such methods have limited utility for characterizing populations, variant types or virulence traits of pathogens. Whole genome sequencing (WGS) can be used to determine this information. However, pathogens must be isolated and cultured to yield sufficient DNA for WGS, which is laborious or not feasible for certain stages of parasites like oocysts of Toxoplasma gondii. We previously developed the Circular Nucleic acid Enrichment Reagent (CNER) method to make whole genome enrichment (WGE) baits for difficult-to-grow bacterial pathogens. WGE using CNERs facilitates direct sequencing of pathogens from samples without the need to isolate and grow them. Here, we made WGE-CNERs for T. gondii to demonstrate the use of the CNER method to make baits to enrich the large genomes of water and foodborne protozoan pathogens. By sequencing, we detected as few as 50 parasites spiked in an oyster hemolymph matrix. We discuss the use of WGE-CNERs for genomic surveillance of food and waterborne pathogens.
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Affiliation(s)
| | - Karen Shapiro
- One Health Institute, UC Davis, USA; Department of Pathology, Microbiology, and Immunology, UC Davis, USA.
| | | | - Lauren E Camp
- Department of Pathology, Microbiology, and Immunology, UC Davis, USA
| | - Rachel S Meyer
- Department of Ecology and Evolutionary Biology, UC Santa Cruz, USA
| | - Beth Shapiro
- Department of Ecology and Evolutionary Biology, UC Santa Cruz, USA; Howard Hughes Medical Institute, UC Santa Cruz, USA
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2
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Sundararaman B, Sylvester MD, Kozyreva VK, Berrada ZL, Corbett-Detig RB, Green RE. A hybridization target enrichment approach for pathogen genomics. mBio 2023; 14:e0188923. [PMID: 37830873 PMCID: PMC10653935 DOI: 10.1128/mbio.01889-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 09/08/2023] [Indexed: 10/14/2023] Open
Abstract
IMPORTANCE Emerging infectious diseases require continuous pathogen monitoring. Rapid clinical diagnosis by nucleic acid amplification is limited to a small number of targets and may miss target detection due to new mutations in clinical isolates. Whole-genome sequencing (WGS) identifies genome-wide variations that may be used to determine a pathogen's drug resistance patterns and phylogenetically characterize isolates to track disease origin and transmission. WGS is typically performed using DNA isolated from cultured clinical isolates. Culturing clinical specimens increases turn-around time and may not be possible for fastidious bacteria. To overcome some of these limitations, direct sequencing of clinical specimens has been attempted using expensive capture probes to enrich the entire genomes of target pathogens. We present a method to produce a cost-effective, time-efficient, and large-scale synthesis of probes for whole-genome enrichment. We envision that our method can be used for direct clinical sequencing of a wide range of microbial pathogens for genomic epidemiology.
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Affiliation(s)
- Balaji Sundararaman
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, California, USA
| | - Matthew D. Sylvester
- Center for Laboratory Sciences, California Department of Public Health, Microbial Diseases Laboratory Branch, Richmond, California, USA
| | - Varvara K. Kozyreva
- Center for Laboratory Sciences, California Department of Public Health, Microbial Diseases Laboratory Branch, Richmond, California, USA
| | - Zenda L. Berrada
- Center for Laboratory Sciences, California Department of Public Health, Microbial Diseases Laboratory Branch, Richmond, California, USA
| | - Russell B. Corbett-Detig
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, California, USA
- UCSC Genomics Institute, University of California Santa Cruz, Santa Cruz, California, USA
| | - Richard E. Green
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, California, USA
- UCSC Genomics Institute, University of California Santa Cruz, Santa Cruz, California, USA
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3
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Beyond microbial core genomic epidemiology: towards pan genomic epidemiology. THE LANCET MICROBE 2022; 3:e244-e245. [DOI: 10.1016/s2666-5247(22)00058-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 02/21/2022] [Indexed: 02/05/2023] Open
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Xu Y, Stockdale JE, Naidu V, Hatherell H, Stimson J, Stagg HR, Abubakar I, Colijn C. Transmission analysis of a large tuberculosis outbreak in London: a mathematical modelling study using genomic data. Microb Genom 2020; 6:mgen000450. [PMID: 33174832 PMCID: PMC7725332 DOI: 10.1099/mgen.0.000450] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 09/15/2020] [Indexed: 12/11/2022] Open
Abstract
Outbreaks of tuberculosis (TB) - such as the large isoniazid-resistant outbreak centred on London, UK, which originated in 1995 - provide excellent opportunities to model transmission of this devastating disease. Transmission chains for TB are notoriously difficult to ascertain, but mathematical modelling approaches, combined with whole-genome sequencing data, have strong potential to contribute to transmission analyses. Using such data, we aimed to reconstruct transmission histories for the outbreak using a Bayesian approach, and to use machine-learning techniques with patient-level data to identify the key covariates associated with transmission. By using our transmission reconstruction method that accounts for phylogenetic uncertainty, we are able to identify 21 transmission events with reasonable confidence, 9 of which have zero SNP distance, and a maximum distance of 3. Patient age, alcohol abuse and history of homelessness were found to be the most important predictors of being credible TB transmitters.
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Affiliation(s)
- Yuanwei Xu
- Centre for Mathematics of Precision Healthcare, Department of Mathematics, Imperial College London, London, UK
| | | | - Vijay Naidu
- Department of Mathematics, Simon Fraser University, Burnaby, BC V5A 1S6, Canada
| | | | - James Stimson
- Centre for Mathematics of Precision Healthcare, Department of Mathematics, Imperial College London, London, UK
- National Infection Service, Public Health England, London, UK
| | - Helen R. Stagg
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Ibrahim Abubakar
- Institute for Global Health, University College London, London, UK
| | - Caroline Colijn
- Centre for Mathematics of Precision Healthcare, Department of Mathematics, Imperial College London, London, UK
- Department of Mathematics, Simon Fraser University, Burnaby, BC V5A 1S6, Canada
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Hamelin RC, Roe AD. Genomic biosurveillance of forest invasive alien enemies: A story written in code. Evol Appl 2020; 13:95-115. [PMID: 31892946 PMCID: PMC6935587 DOI: 10.1111/eva.12853] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2019] [Revised: 06/30/2019] [Accepted: 07/19/2019] [Indexed: 12/15/2022] Open
Abstract
The world's forests face unprecedented threats from invasive insects and pathogens that can cause large irreversible damage to the ecosystems. This threatens the world's capacity to provide long-term fiber supply and ecosystem services that range from carbon storage, nutrient cycling, and water and air purification, to soil preservation and maintenance of wildlife habitat. Reducing the threat of forest invasive alien species requires vigilant biosurveillance, the process of gathering, integrating, interpreting, and communicating essential information about pest and pathogen threats to achieve early detection and warning and to enable better decision-making. This process is challenging due to the diversity of invasive pests and pathogens that need to be identified, the diverse pathways of introduction, and the difficulty in assessing the risk of establishment. Genomics can provide powerful new solutions to biosurveillance. The process of invasion is a story written in four chapters: transport, introduction, establishment, and spread. The series of processes that lead to a successful invasion can leave behind a DNA signature that tells the story of an invasion. This signature can help us understand the dynamic, multistep process of invasion and inform management of current and future introductions. This review describes current and future application of genomic tools and pipelines that will provide accurate identification of pests and pathogens, assign outbreak or survey samples to putative sources to identify pathways of spread, and assess risk based on traits that impact the outbreak outcome.
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Affiliation(s)
- Richard C. Hamelin
- Department of Forest and Conservation SciencesThe University of British ColumbiaVancouverBCCanada
- Institut de Biologie Intégrative et des Systèmes (IBIS)Université LavalQuébecQCCanada
- Département des sciences du bois et de la forêt, Faculté de Foresterie et GéographieUniversité LavalQuébecQCCanada
| | - Amanda D. Roe
- Great Lakes Forestry CenterNatural Resources CanadaSault Ste. MarieONCanada
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Radomski N, Cadel-Six S, Cherchame E, Felten A, Barbet P, Palma F, Mallet L, Le Hello S, Weill FX, Guillier L, Mistou MY. A Simple and Robust Statistical Method to Define Genetic Relatedness of Samples Related to Outbreaks at the Genomic Scale - Application to Retrospective Salmonella Foodborne Outbreak Investigations. Front Microbiol 2019; 10:2413. [PMID: 31708892 PMCID: PMC6821717 DOI: 10.3389/fmicb.2019.02413] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Accepted: 10/07/2019] [Indexed: 12/21/2022] Open
Abstract
The investigation of foodborne outbreaks (FBOs) from genomic data typically relies on inspecting the relatedness of samples through a phylogenomic tree computed on either SNPs, genes, kmers, or alleles (i.e., cgMLST and wgMLST). The phylogenomic reconstruction is often time-consuming, computation-intensive and depends on hidden assumptions, pipelines implementation and their parameterization. In the context of FBO investigations, robust links between isolates are required in a timely manner to trigger appropriate management actions. Here, we propose a non-parametric statistical method to assert the relatedness of samples (i.e., outbreak cases) or whether to reject them (i.e., non-outbreak cases). With typical computation running within minutes on a desktop computer, we benchmarked the ability of three non-parametric statistical tests (i.e., Wilcoxon rank-sum, Kolmogorov-Smirnov and Kruskal-Wallis) on six different genomic features (i.e., SNPs, SNPs excluding recombination events, genes, kmers, cgMLST alleles, and wgMLST alleles) to discriminate outbreak cases (i.e., positive control: C+) from non-outbreak cases (i.e., negative control: C-). We leveraged four well-characterized and retrospectively investigated FBOs of Salmonella Typhimurium and its monophasic variant S. 1,4,[5],12:i:- from France, setting positive and negative controls in all the assays. We show that the approaches relying on pairwise SNP differences distinguished all four considered outbreaks in contrast to the other tested genomic features (i.e., genes, kmers, cgMLST alleles, and wgMLST alleles). The freely available non-parametric method written in R has been designed to be independent of both the phylogenomic reconstruction and the detection methods of genomic features (i.e., SNPs, genes, kmers, or alleles), making it widely and easily usable to anybody working on genomic data from suspected samples.
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Affiliation(s)
- Nicolas Radomski
- ANSES, Laboratory for Food Safety, Université PARIS-EST, Maisons-Alfort, France
| | - Sabrina Cadel-Six
- ANSES, Laboratory for Food Safety, Université PARIS-EST, Maisons-Alfort, France
| | - Emeline Cherchame
- ANSES, Laboratory for Food Safety, Université PARIS-EST, Maisons-Alfort, France
| | - Arnaud Felten
- ANSES, Laboratory for Food Safety, Université PARIS-EST, Maisons-Alfort, France
| | - Pauline Barbet
- ANSES, Laboratory for Food Safety, Université PARIS-EST, Maisons-Alfort, France
| | - Federica Palma
- ANSES, Laboratory for Food Safety, Université PARIS-EST, Maisons-Alfort, France
| | - Ludovic Mallet
- ANSES, Laboratory for Food Safety, Université PARIS-EST, Maisons-Alfort, France
| | - Simon Le Hello
- Unité des Bactéries Pathogènes Entériques, Institut Pasteur, Centre National de Référence des Salmonella, Paris, France
| | - François-Xavier Weill
- Unité des Bactéries Pathogènes Entériques, Institut Pasteur, Centre National de Référence des Salmonella, Paris, France
| | - Laurent Guillier
- ANSES, Laboratory for Food Safety, Université PARIS-EST, Maisons-Alfort, France
| | - Michel-Yves Mistou
- ANSES, Laboratory for Food Safety, Université PARIS-EST, Maisons-Alfort, France
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Mintzer V, Moran-Gilad J, Simon-Tuval T. Operational models and criteria for incorporating microbial whole genome sequencing in hospital microbiology - A systematic literature review. Clin Microbiol Infect 2019; 25:1086-1095. [PMID: 31039443 DOI: 10.1016/j.cmi.2019.04.019] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2019] [Revised: 04/17/2019] [Accepted: 04/18/2019] [Indexed: 12/12/2022]
Abstract
BACKGROUND Microbial whole genome sequencing (WGS) has many advantages over standard microbiological methods. However, it is not yet widely implemented in routine hospital diagnostics due to notable challenges. OBJECTIVES The aim was to extract managerial, financial and clinical criteria supporting the decision to implement WGS in routine diagnostic microbiology, across different operational models of implementation in the hospital setting. METHODS This was a systematic review of literature identified through PubMed and Web of Science. English literature studies discussing the applications of microbial WGS without limitation on publication date were eligible. A narrative approach for categorization and synthesis of the sources identified was adopted. RESULTS A total of 98 sources were included. Four main alternative operational models for incorporating WGS in clinical microbiology laboratories were identified: full in-house sequencing and analysis, full outsourcing of sequencing and analysis and two hybrid models combining in-house/outsourcing of the sequencing and analysis components. Six main criteria (and multiple related sub-criteria) for WGS implementation emerged from our review and included cost (e.g. the availability of resources for capital and operational investment); manpower (e.g. the ability to provide training programmes or recruit trained personnel), laboratory infrastructure (e.g. the availability of supplies and consumables or sequencing platforms), bioinformatics requirements (e.g. the availability of valid analysis tools); computational infrastructure (e.g. the availability of storage space or data safety arrangements); and quality control (e.g. the existence of standardized procedures). CONCLUSIONS The decision to incorporate WGS in routine diagnostics involves multiple, sometimes competing, criteria and sub-criteria. Mapping these criteria systematically is an essential stage in developing policies for adoption of this technology, e.g. using a multicriteria decision tool. Future research that will prioritize criteria and sub-criteria that were identified in our review in the context of operational models will inform decision-making at clinical and managerial levels with respect to effective implementation of WGS for routine use. Beyond WGS, similar decision-making challenges are expected with respect to future integration of clinical metagenomics.
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Affiliation(s)
- V Mintzer
- Department of Health Systems Management, Guilford Glazer Faculty of Business and Management and Faculty of Health Sciences, Ben-Gurion University of the Negev, Israel; Leumit Health Services, Israel
| | - J Moran-Gilad
- Department of Health Policy and Management, School of Public Health, Faculty of Health Sciences, Ben-Gurion University of the Negev, Israel; ESCMID Study Group for Genomic and Molecular Diagnostics (ESGMD), Basel, Switzerland
| | - T Simon-Tuval
- Department of Health Systems Management, Guilford Glazer Faculty of Business and Management and Faculty of Health Sciences, Ben-Gurion University of the Negev, Israel.
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Lees JA, Kendall M, Parkhill J, Colijn C, Bentley SD, Harris SR. Evaluation of phylogenetic reconstruction methods using bacterial whole genomes: a simulation based study. Wellcome Open Res 2018. [DOI: 10.12688/wellcomeopenres.14265.1] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Background: Phylogenetic reconstruction is a necessary first step in many analyses which use whole genome sequence data from bacterial populations. There are many available methods to infer phylogenies, and these have various advantages and disadvantages, but few unbiased comparisons of the range of approaches have been made. Methods: We simulated data from a defined “true tree” using a realistic evolutionary model. We built phylogenies from this data using a range of methods, and compared reconstructed trees to the true tree using two measures, noting the computational time needed for different phylogenetic reconstructions. We also used real data from Streptococcus pneumoniae alignments to compare individual core gene trees to a core genome tree. Results: We found that, as expected, maximum likelihood trees from good quality alignments were the most accurate, but also the most computationally intensive. Using less accurate phylogenetic reconstruction methods, we were able to obtain results of comparable accuracy; we found that approximate results can rapidly be obtained using genetic distance based methods. In real data we found that highly conserved core genes, such as those involved in translation, gave an inaccurate tree topology, whereas genes involved in recombination events gave inaccurate branch lengths. We also show a tree-of-trees, relating the results of different phylogenetic reconstructions to each other. Conclusions: We recommend three approaches, depending on requirements for accuracy and computational time. Quicker approaches that do not perform full maximum likelihood optimisation may be useful for many analyses requiring a phylogeny, as generating a high quality input alignment is likely to be the major limiting factor of accurate tree topology. We have publicly released our simulated data and code to enable further comparisons.
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Lees JA, Kendall M, Parkhill J, Colijn C, Bentley SD, Harris SR. Evaluation of phylogenetic reconstruction methods using bacterial whole genomes: a simulation based study. Wellcome Open Res 2018; 3:33. [PMID: 29774245 PMCID: PMC5930550 DOI: 10.12688/wellcomeopenres.14265.2] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/20/2018] [Indexed: 12/28/2022] Open
Abstract
Background: Phylogenetic reconstruction is a necessary first step in many analyses which use whole genome sequence data from bacterial populations. There are many available methods to infer phylogenies, and these have various advantages and disadvantages, but few unbiased comparisons of the range of approaches have been made. Methods: We simulated data from a defined 'true tree' using a realistic evolutionary model. We built phylogenies from this data using a range of methods, and compared reconstructed trees to the true tree using two measures, noting the computational time needed for different phylogenetic reconstructions. We also used real data from
Streptococcus pneumoniae alignments to compare individual core gene trees to a core genome tree. Results: We found that, as expected, maximum likelihood trees from good quality alignments were the most accurate, but also the most computationally intensive. Using less accurate phylogenetic reconstruction methods, we were able to obtain results of comparable accuracy; we found that approximate results can rapidly be obtained using genetic distance based methods. In real data we found that highly conserved core genes, such as those involved in translation, gave an inaccurate tree topology, whereas genes involved in recombination events gave inaccurate branch lengths. We also show a tree-of-trees, relating the results of different phylogenetic reconstructions to each other. Conclusions: We recommend three approaches, depending on requirements for accuracy and computational time. For the most accurate tree, use of either RAxML or IQ-TREE with an alignment of variable sites produced by mapping to a reference genome is best. Quicker approaches that do not perform full maximum likelihood optimisation may be useful for many analyses requiring a phylogeny, as generating a high quality input alignment is likely to be the major limiting factor of accurate tree topology. We have publicly released our simulated data and code to enable further comparisons.
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Affiliation(s)
- John A Lees
- Infection Genomics, Wellcome Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK.,Department of Microbiology, New York School of Medicine, New York, 10016, USA
| | - Michelle Kendall
- Department of Mathematics, Imperial College London, London, SW7 2AZ, UK
| | - Julian Parkhill
- Infection Genomics, Wellcome Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK
| | - Caroline Colijn
- Department of Mathematics, Imperial College London, London, SW7 2AZ, UK
| | - Stephen D Bentley
- Infection Genomics, Wellcome Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK
| | - Simon R Harris
- Infection Genomics, Wellcome Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK
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Infection control in the new age of genomic epidemiology. Am J Infect Control 2017; 45:170-179. [PMID: 28159067 DOI: 10.1016/j.ajic.2016.05.015] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2016] [Revised: 05/22/2016] [Accepted: 05/23/2016] [Indexed: 12/25/2022]
Abstract
With the growing importance of infectious diseases in health care and communicable disease outbreaks garnering increasing attention, new technologies are playing a greater role in helping us prevent health care-associated infections and provide optimal public health. The microbiology laboratory has always played a large role in infection control by providing tools to identify, characterize, and track pathogens. Recently, advances in DNA sequencing technology have ushered in a new era of genomic epidemiology, where traditional molecular diagnostics and genotyping methods are being enhanced and even replaced by genomics-based methods to aid epidemiologic investigations of communicable diseases. The ability to analyze and compare entire pathogen genomes has allowed for unprecedented resolution into how and why infectious diseases spread. As these genomics-based methods continue to improve in speed, cost, and accuracy, they will be increasingly used to inform and guide infection control and public health practices.
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Chan CH, Octavia S, Sintchenko V, Lan R. SnpFilt: A pipeline for reference-free assembly-based identification of SNPs in bacterial genomes. Comput Biol Chem 2016; 65:178-184. [DOI: 10.1016/j.compbiolchem.2016.09.004] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2016] [Accepted: 09/07/2016] [Indexed: 10/21/2022]
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