91 results found
Hall M, Colijn C, 2019, Transmission trees on a known pathogen phylogeny: enumeration and sampling., Mol Biol Evol
One approach to the reconstruction of infectious disease transmission trees from pathogen genomic data has been to use a phylogenetic tree, reconstructed from pathogen sequences, and annotate its internal nodes to provide a reconstruction of which host each lineage was in at each point in time. If only one pathogen lineage can be transmitted to a new host (i.e. the transmission bottleneck is complete), this corresponds to partitioning the nodes of the phylogeny into connected regions, each of which represents evolution in an individual host. These partitions define the possible transmission trees that are consistent with a given phylogenetic tree. However, the mathematical properties of the transmission trees given a phylogeny remain largely unexplored. Here, we describe a procedure to calculate the number of possible transmission trees for a given phylogeny, and we then show how to uniformly sample from these transmission trees. The procedure is outlined for situations where one sample is available from each host and trees do not have branch lengths, and we also provide extensions for incomplete sampling, multiple sampling, and the application to time trees in a situation where limits on the period during which each host could have been infected and infectious are known. The sampling algorithm is available as an R package (STraTUS).
Stimson J, Gardy J, Mathema B, et al., 2019, Beyond the SNP Threshold: Identifying Outbreak Clusters Using Inferred Transmissions, MOLECULAR BIOLOGY AND EVOLUTION, Vol: 36, Pages: 587-603, ISSN: 0737-4038
Mabud TS, de Lourdes Delgado Alves M, Ko AI, et al., 2019, Correction: Evaluating strategies for control of tuberculosis in prisons and prevention of spillover into communities: An observational and modeling study from Brazil., PLoS Med, Vol: 16
[This corrects the article DOI: 10.1371/journal.pmed.1002737.].
Mabud TS, Delgado Alves MDL, Ko AI, et al., 2019, Evaluating strategies for control of tuberculosis in prisons and prevention of spillover into communities: An observational and modeling study from Brazil, PLOS MEDICINE, Vol: 16, ISSN: 1549-1676
Ayabina D, Ronning JO, Alfsnes K, et al., 2018, Genome-based transmission modelling separates imported tuberculosis from recent transmission within an immigrant population, MICROBIAL GENOMICS, Vol: 4, ISSN: 2057-5858
Yang C, Lu L, Warren JL, et al., 2018, Internal migration and transmission dynamics of tuberculosis in Shanghai, China: an epidemiological, spatial, genomic analysis, LANCET INFECTIOUS DISEASES, Vol: 18, Pages: 788-795, ISSN: 1473-3099
Kendall ML, Ayabina P, Xu Y, et al., 2018, Estimating Transmission from Genetic and Epidemiological Data: A Metric to Compare Transmission Trees, Statistical Science, Vol: 33, Pages: 70-85, ISSN: 0883-4237
Reconstructing who infected whom is a central challenge in analysing epidemiological data. Recently, advances in sequencing technology have led to increasing interest in Bayesian approaches to inferring who infected whom using genetic data from pathogens. The logic behind such approaches is that isolates that are nearly genetically identical are more likely to have been recently transmitted than those that are very different. A number of methods have been developed to perform this inference. However, testing their convergence, examining posterior sets of transmission trees and comparing methods’ performance are challenged by the fact that the object of inference—the transmission tree—is a complicated discrete structure. We introduce a metric on transmission trees to quantify distances between them. The metric can accommodate trees with unsampled individuals, and highlights differences in the source case and in the number of infections per infector. We illustrate its performance on simple simulated scenarios and on posterior transmission trees from a TB outbreak. We find that the metric reveals where the posterior is sensitive to the priors, and where collections of trees are composed of distinct clusters. We use the metric to define median trees summarising these clusters. Quantitative tools to compare transmission trees to each other will be required for assessing MCMC convergence, exploring posterior trees and benchmarking diverse methods as this field continues to mature.
Kendall M, Ayabina D, Xu Y, et al., 2018, Estimating Transmission from Genetic and Epidemiological Data: A Metric to Compare Transmission Trees, Publisher: INST MATHEMATICAL STATISTICS
Colijn C, Plazzotta G, 2018, A Metric on Phylogenetic Tree Shapes, SYSTEMATIC BIOLOGY, Vol: 67, Pages: 113-126, ISSN: 1063-5157
Yaesoubi R, Trotter C, Colijn C, et al., 2018, The cost-effectiveness of alternative vaccination strategies for polyvalent meningococcal vaccines in Burkina Faso: A transmission dynamic modeling study, PLOS MEDICINE, Vol: 15, ISSN: 1549-1676
Lees JA, Kendall M, Parkhill J, et al., 2018, Evaluation of phylogenetic reconstruction methods using bacterial whole genomes: a simulation based study., Wellcome Open Res, Vol: 3, ISSN: 2398-502X
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.
Grandjean L, Gilman RH, Iwamoto T, et al., 2017, Convergent evolution and topologically disruptive polymorphisms among multidrug-resistant tuberculosis in Peru, PLOS ONE, Vol: 12, ISSN: 1932-6203
Ratmann O, Wymant C, Colijn C, et al., 2017, HIV-1 Full-Genome Phylogenetics of Generalized Epidemics in Sub-Saharan Africa: Impact of Missing Nucleotide Characters in Next-Generation Sequences, AIDS RESEARCH AND HUMAN RETROVIRUSES, Vol: 33, Pages: 1083-1098, ISSN: 0889-2229
Jombart T, Kendall M, Almagro-Garcia J, et al., 2017, treespace: Statistical exploration of landscapes of phylogenetic trees, MOLECULAR ECOLOGY RESOURCES, Vol: 17, Pages: 1385-1392, ISSN: 1755-098X
Sartelli M, Weber DG, Ruppe E, et al., 2017, Antimicrobials: a global alliance for optimizing their rational use in intra-abdominal infections (AGORA) (vol 11, 33, 2016), WORLD JOURNAL OF EMERGENCY SURGERY, Vol: 12, ISSN: 1749-7922
Cobey S, Baskerville EB, Colijn C, et al., 2017, Host population structure and treatment frequency maintain balancing selection on drug resistance, JOURNAL OF THE ROYAL SOCIETY INTERFACE, Vol: 14, ISSN: 1742-5689
Fyson N, King J, Belcher T, et al., 2017, A curated genome-scale metabolic model of Bordetella pertussis metabolism, PLOS COMPUTATIONAL BIOLOGY, Vol: 13, ISSN: 1553-734X
Klinkenberg D, Backer JA, Didelot X, et al., 2017, Simultaneous inference of phylogenetic and transmission trees in infectious disease outbreaks, PLOS COMPUTATIONAL BIOLOGY, Vol: 13, ISSN: 1553-734X
Didelot X, Fraser C, Gardy J, et al., 2017, Genomic Infectious Disease Epidemiology in Partially Sampled and Ongoing Outbreaks, MOLECULAR BIOLOGY AND EVOLUTION, Vol: 34, Pages: 997-1007, ISSN: 0737-4038
Colijn C, Jones N, Johnston IG, et al., 2017, Toward Precision Healthcare: Context and Mathematical Challenges, FRONTIERS IN PHYSIOLOGY, Vol: 8, ISSN: 1664-042X
Ratmann O, Hodcroft EB, Pickles M, et al., 2017, Phylogenetic Tools for Generalized HIV-1 Epidemics: Findings from the PANGEA-HIV Methods Comparison, MOLECULAR BIOLOGY AND EVOLUTION, Vol: 34, Pages: 185-203, ISSN: 0737-4038
Plazzotta G, Colijn C, 2016, ASYMPTOTIC FREQUENCY OF SHAPES IN SUPERCRITICAL BRANCHING TREES, Publisher: CAMBRIDGE UNIV PRESS
Ayabina D, Hendon-Dunn C, Bacon J, et al., 2016, Diverse drug-resistant subpopulations of Mycobacterium tuberculosis are sustained in continuous culture, JOURNAL OF THE ROYAL SOCIETY INTERFACE, Vol: 13, ISSN: 1742-5689
Kendall M, Colijn C, 2016, Mapping Phylogenetic Trees to Reveal Distinct Patterns of Evolution, MOLECULAR BIOLOGY AND EVOLUTION, Vol: 33, Pages: 2735-2743, ISSN: 0737-4038
Sartelli M, Weber DG, Ruppe E, et al., 2016, Antimicrobials: a global alliance for optimizing their rational use in intra-abdominal infections (AGORA), WORLD JOURNAL OF EMERGENCY SURGERY, Vol: 11, ISSN: 1749-7922
Aanensen DM, Feil EJ, Holden MTG, et al., 2016, Whole-Genome Sequencing for Routine Pathogen Surveillance in Public Health: a Population Snapshot of Invasive Staphylococcus aureus in Europe, MBIO, Vol: 7, ISSN: 2150-7511
Hatherell H-A, Didelot X, Pollock SL, et al., 2016, Declaring a tuberculosis outbreak over with genomic epidemiology, MICROBIAL GENOMICS, Vol: 2, ISSN: 2057-5858
Kendall ML, Boyd M, Colijn C, 2016, phyloTop
Tools for calculating and viewing topological properties of phylogenetic trees.
Hatherell H-A, Colijn C, Stagg HR, et al., 2016, Interpreting whole genome sequencing for investigating tuberculosis transmission: a systematic review, BMC MEDICINE, Vol: 14, ISSN: 1741-7015
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