64 results found
Beugin M-P, Gayet T, Pontier D, et al., 2018, A fast likelihood solution to the genetic clustering problem, Methods in Ecology and Evolution, ISSN: 2041-210X
The investigation of genetic clusters in natural populations is an ubiquitous problem in a range of fields relying on the analysis of genetic data, such as molecular ecology, conservation biology and microbiology. Typically, genetic clusters are defined as distinct panmictic populations, or parental groups in the context of hybridisation. Two types of methods have been developed for identifying such clusters: model-based methods, which are usually computer-intensive but yield results which can be interpreted in the light of an explicit population genetic model, and geometric approaches, which are less interpretable but remarkably faster.Here, we introduce snapclust, a fast maximum-likelihood solution to the genetic clustering problem, which allies the advantages of both model-based and geometric approaches. Our method relies on maximising the likelihood of a fixed number of panmictic populations, using a combination of geometric approach and fast likelihood optimisation, using the Expectation-Maximisation (EM) algorithm. It can be used for assigning genotypes to populations and optionally identify various types of hybrids between two parental populations. Several goodness-of-fit statistics can also be used to guide the choice of the retained number of clusters.Using extensive simulations, we show that snapclust performs comparably to current gold standards for genetic clustering as well as hybrid detection, with some advantages for identifying hybrids after several backcrosses, while being orders of magnitude faster than other model-based methods. We also illustrate how snapclust can be used for identifying the optimal number of clusters, and subsequently assign individuals to various hybrid classes simulated from an empirical microsatellite dataset.snapclust is implemented in the package adegenet for the free software R, and is therefore easily integrated into existing pipelines for genetic data analysis. It can be applied to any kind of co-dominant markers, and ca
Bertranpetit E, Jombart T, Paradis E, et al., 2017, Phylogeography of Toxoplasma gondii points to a South American origin, INFECTION GENETICS AND EVOLUTION, Vol: 48, Pages: 150-155, ISSN: 1567-1348
Cori A, Donnelly CA, Dorigatti I, et al., 2017, Key data for outbreak evaluation: building on the Ebola experience, PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, Vol: 372, ISSN: 0962-8436
Dupuis JR, Bremer FT, Jombart T, et al., 2017, mvmapper: Interactive spatial mapping of genetic structures., Mol Ecol Resour
Characterizing genetic structure across geographic space is a fundamental challenge in population genetics. Multivariate statistical analyses are powerful tools for summarizing genetic variability, but geographic information and accompanying metadata are not always easily integrated into these methods in a user-friendly fashion. Here, we present a deployable Python-based web-tool, mvmapper, for visualizing and exploring results of multivariate analyses in geographic space. This tool can be used to map results of virtually any multivariate analysis of georeferenced data, and routines for exporting results from a number of standard methods have been integrated in the R package adegenet, including principal components analysis (PCA), spatial PCA, discriminant analysis of principal components, principal coordinates analysis, nonmetric dimensional scaling and correspondence analysis. mvmapper's greatest strength is facilitating dynamic and interactive exploration of the statistical and geographic frameworks side by side, a task that is difficult and time-consuming with currently available tools. Source code and deployment instructions, as well as a link to a hosted instance of mvmapper, can be found at https://popphylotools.github.io/mvMapper/.
Garske T, Cori A, Ariyarajah A, et al., 2017, Heterogeneities in the case fatality ratio in the West African Ebola outbreak 2013-2016, PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, Vol: 372, ISSN: 0962-8436
Inns T, Ashton PM, Herrera-Leon S, et al., 2017, Prospective use of whole genome sequencing (WGS) detected a multi-country outbreak of Salmonella Enteritidis, EPIDEMIOLOGY AND INFECTION, Vol: 145, Pages: 289-298, ISSN: 0950-2688
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
Montano V, Jombart T, 2017, An Eigenvalue test for spatial principal component analysis, BMC BIOINFORMATICS, Vol: 18, ISSN: 1471-2105
Nouvellet P, Cori A, Garske T, et al., 2017, A simple approach to measure transmissibility and forecast incidence., Epidemics
Outbreaks of novel pathogens such as SARS, pandemic influenza and Ebola require substantial investments in reactive interventions, with consequent implementation plans sometimes revised on a weekly basis. Therefore, short-term forecasts of incidence are often of high priority. In light of the recent Ebola epidemic in West Africa, a forecasting exercise was convened by a network of infectious disease modellers. The challenge was to forecast unseen "future" simulated data for four different scenarios at five different time points. In a similar method to that used during the recent Ebola epidemic, we estimated current levels of transmissibility, over variable time-windows chosen in an ad hoc way. Current estimated transmissibility was then used to forecast near-future incidence. We performed well within the challenge and often produced accurate forecasts. A retrospective analysis showed that our subjective method for deciding on the window of time with which to estimate transmissibility often resulted in the optimal choice. However, when near-future trends deviated substantially from exponential patterns, the accuracy of our forecasts was reduced. This exercise highlights the urgent need for infectious disease modellers to develop more robust descriptions of processes - other than the widespread depletion of susceptible individuals - that produce non-exponential patterns of incidence.
Paradis E, Gosselin T, Grunwald NJ, et al., 2017, Towards an integrated ecosystem of R packages for the analysis of population genetic data, MOLECULAR ECOLOGY RESOURCES, Vol: 17, Pages: 1-4, ISSN: 1755-098X
Agua-Agum J, Allegranzi B, Ariyarajah A, et al., 2016, After Ebola in West Africa - Unpredictable Risks, Preventable Epidemics, NEW ENGLAND JOURNAL OF MEDICINE, Vol: 375, Pages: 587-596, ISSN: 0028-4793
Agua-Agum J, Ariyarajah A, Aylward B, et al., 2016, Exposure Patterns Driving Ebola Transmission in West Africa: A Retrospective Observational Study, PLOS MEDICINE, Vol: 13, ISSN: 1549-1676
Agua-Agum J, Ariyarajah A, Blake IM, et al., 2016, Ebola Virus Disease among Male and Female Persons in West Africa, NEW ENGLAND JOURNAL OF MEDICINE, Vol: 374, Pages: 96-98, ISSN: 0028-4793
Cauchemez S, Nouvellet P, Cori A, et al., 2016, Unraveling the drivers of MERS-CoV transmission, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, Vol: 113, Pages: 9081-9086, ISSN: 0027-8424
Clare FC, Halder JB, Daniel O, et al., 2016, Climate forcing of an emerging pathogenic fungus across a montane multi-host community, PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, Vol: 371, ISSN: 0962-8436
Dallman T, Inns T, Jombart T, et al., 2016, Phylogenetic structure of EuropeanSalmonellaEnteritidis outbreak correlates with national and international egg distribution network., Microb Genom, Vol: 2, ISSN: 2057-5858
Outbreaks ofSalmonellaEnteritidis have long been associated with contaminated poultry and eggs. In the summer of 2014 a large multi-national outbreak ofSalmonellaEnteritidis phage type 14b occurred with over 350 cases reported in the United Kingdom, Germany, Austria, France and Luxembourg. Egg supply network investigation and microbiological sampling identified the source to be a Bavarian egg producer. As part of the international investigation into the outbreak, over 400 isolates were sequenced including isolates from cases, implicated UK premises and eggs from the suspected source producer. We were able to show a clear statistical correlation between the topology of the UK egg distribution network and the phylogenetic network of outbreak isolates. This correlation can most plausibly be explained by different parts of the egg distribution network being supplied by eggs solely from independent premises of the Bavarian egg producer (Company X). Microbiological sampling from the source premises, traceback information and information on the interventions carried out at the egg production premises all supported this conclusion. The level of insight into the outbreak epidemiology provided by whole-genome sequencing (WGS) would not have been possible using traditional microbial typing methods.
Karkey A, Jombart T, Walker AW, et al., 2016, The Ecological Dynamics of Fecal Contamination and Salmonella Typhi and Salmonella Paratyphi A in Municipal Kathmandu Drinking Water, PLOS NEGLECTED TROPICAL DISEASES, Vol: 10, ISSN: 1935-2735
Lessler J, Salje H, Van Kerkhove MD, et al., 2016, Estimating the Severity and Subclinical Burden of Middle East Respiratory Syndrome Coronavirus Infection in the Kingdom of Saudi Arabia, AMERICAN JOURNAL OF EPIDEMIOLOGY, Vol: 183, Pages: 657-663, ISSN: 0002-9262
Hao CT, Karkey A, Duy PT, et al., 2015, A high-resolution genomic analysis of multidrug-resistant hospital outbreaks of Klebsiella pneumoniae, EMBO MOLECULAR MEDICINE, Vol: 7, Pages: 227-239, ISSN: 1757-4676
Jombart T, Kendall ML, Almagro-Garcia J, et al., 2015, treespace
Statistical Exploration of Landscapes of Phylogenetic Trees
Mita T, Jombart T, 2015, Patterns and dynamics of genetic diversity in Plasmodium falciparum: What past human migrations tell us about malaria, PARASITOLOGY INTERNATIONAL, Vol: 64, Pages: 238-243, ISSN: 1383-5769
Nhung NT, Cuong NV, Campbell J, et al., 2015, High Levels of Antimicrobial Resistance among Escherichia coli Isolates from Livestock Farms and Synanthropic Rats and Shrews in the Mekong Delta of Vietnam, APPLIED AND ENVIRONMENTAL MICROBIOLOGY, Vol: 81, Pages: 812-820, ISSN: 0099-2240
Nouvellet P, Garske T, Mills HL, et al., 2015, The role of rapid diagnostics in managing Ebola epidemics, NATURE, Vol: 528, Pages: S109-S116, ISSN: 0028-0836
Tong SYC, Holden MTG, Nickerson EK, et al., 2015, Genome sequencing defines phylogeny and spread of methicillin-resistant Staphylococcus aureus in a high transmission setting, GENOME RESEARCH, Vol: 25, Pages: 111-118, ISSN: 1088-9051
Weinert LA, Chaudhuri RR, Wang J, et al., 2015, Genomic signatures of human and animal disease in the zoonotic pathogen Streptococcus suis (vol 6, 6740, 2015), NATURE COMMUNICATIONS, Vol: 6, ISSN: 2041-1723
Weinert LA, Chaudhuri RR, Wang J, et al., 2015, Genomic signatures of human and animal disease in the zoonotic pathogen Streptococcus suis, NATURE COMMUNICATIONS, Vol: 6, ISSN: 2041-1723
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