Imperial College London

DrCarolineColijn

Faculty of Natural SciencesDepartment of Mathematics

Visiting Professor
 
 
 
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Contact

 

+44 (0)20 7594 2647c.colijn Website

 
 
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Location

 

626Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

90 results found

Stimson J, Gardy J, Mathema B, Crudu V, Cohen T, Colijn Cet al., 2019, Beyond the SNP Threshold: Identifying Outbreak Clusters Using Inferred Transmissions., Mol Biol Evol, Vol: 36, Pages: 587-603

Whole-genome sequencing (WGS) is increasingly used to aid the understanding of pathogen transmission. A first step in analyzing WGS data is usually to define "transmission clusters," sets of cases that are potentially linked by direct transmission. This is often done by including two cases in the same cluster if they are separated by fewer single-nucleotide polymorphisms (SNPs) than a specified threshold. However, there is little agreement as to what an appropriate threshold should be. We propose a probabilistic alternative, suggesting that the key inferential target for transmission clusters is the number of transmissions separating cases. We characterize this by combining the number of SNP differences and the length of time over which those differences have accumulated, using information about case timing, molecular clock, and transmission processes. Our framework has the advantage of allowing for variable mutation rates across the genome and can incorporate other epidemiological data. We use two tuberculosis studies to illustrate the impact of our approach: with British Columbia data by using spatial divisions; with Republic of Moldova data by incorporating antibiotic resistance. Simulation results indicate that our transmission-based method is better in identifying direct transmissions than a SNP threshold, with dissimilarity between clusterings of on average 0.27 bits compared with 0.37 bits for the SNP-threshold method and 0.84 bits for randomly permuted data. These results show that it is likely to outperform the SNP-threshold method where clock rates are variable and sample collection times are spread out. We implement the method in the R package transcluster.

JOURNAL ARTICLE

Mabud TS, de Lourdes Delgado Alves M, Ko AI, Basu S, Walter KS, Cohen T, Mathema B, Colijn C, Lemos E, Croda J, Andrews JRet 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.].

JOURNAL ARTICLE

Metzig C, Ratmann O, Bezemer D, Colijn Cet al., 2019, Phylogenies from dynamic networks., PLoS Comput Biol, Vol: 15

The relationship between the underlying contact network over which a pathogen spreads and the pathogen phylogenetic trees that are obtained presents an opportunity to use sequence data to learn about contact networks that are difficult to study empirically. However, this relationship is not explicitly known and is usually studied in simulations, often with the simplifying assumption that the contact network is static in time, though human contact networks are dynamic. We simulate pathogen phylogenetic trees on dynamic Erdős-Renyi random networks and on two dynamic networks with skewed degree distribution, of which one is additionally clustered. We use tree shape features to explore how adding dynamics changes the relationships between the overall network structure and phylogenies. Our tree features include the number of small substructures (cherries, pitchforks) in the trees, measures of tree imbalance (Sackin index, Colless index), features derived from network science (diameter, closeness), as well as features using the internal branch lengths from the tip to the root. Using principal component analysis we find that the network dynamics influence the shapes of phylogenies, as does the network type. We also compare dynamic and time-integrated static networks. We find, in particular, that static network models like the widely used Barabasi-Albert model can be poor approximations for dynamic networks. We explore the effects of mis-specifying the network on the performance of classifiers trained identify the transmission rate (using supervised learning methods). We find that both mis-specification of the underlying network and its parameters (mean degree, turnover rate) have a strong adverse effect on the ability to estimate the transmission parameter. We illustrate these results by classifying HIV trees with a classifier that we trained on simulated trees from different networks, infection rates and turnover rates. Our results point to the importance of correctly est

JOURNAL ARTICLE

Mabud TS, Delgado Alves MDL, Ko AI, Basu S, Walter KS, Cohen T, Mathema B, Colijn C, Lemos E, Croda J, Andrews JRet 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

JOURNAL ARTICLE

Ayabina D, Ronning JO, Alfsnes K, Debech N, Brynikisrud OB, Arnesen T, Norheim G, Mengshoel A-T, Rykkvin R, Dahle UR, Colijn C, Eldholm Vet al., 2018, Genome-based transmission modelling separates imported tuberculosis from recent transmission within an immigrant population, MICROBIAL GENOMICS, Vol: 4, ISSN: 2057-5858

JOURNAL ARTICLE

Yang C, Lu L, Warren JL, Wu J, Jiang Q, Zuo T, Gan M, Liu M, Liu Q, DeRiemer K, Hong J, Shen X, Colijn C, Guo X, Gao Q, Cohen Tet 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

JOURNAL ARTICLE

Kendall ML, Ayabina P, Xu Y, Stimson J, Colijn Cet 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.

JOURNAL ARTICLE

Kendall M, Ayabina D, Xu Y, Stimson J, Colijn Cet al., 2018, Estimating Transmission from Genetic and Epidemiological Data: A Metric to Compare Transmission Trees, Publisher: INST MATHEMATICAL STATISTICS

WORKING PAPER

Yaesoubi R, Trotter C, Colijn C, Yaesoubi M, Colombini A, Resch S, Kristiansen PA, LaForce FM, Cohen Tet 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

JOURNAL ARTICLE

Colijn C, Plazzotta G, 2018, A Metric on Phylogenetic Tree Shapes, SYSTEMATIC BIOLOGY, Vol: 67, Pages: 113-126, ISSN: 1063-5157

JOURNAL ARTICLE

Lees JA, Kendall M, Parkhill J, Colijn C, Bentley SD, Harris SRet 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.

JOURNAL ARTICLE

Grandjean L, Gilman RH, Iwamoto T, Koser CU, Coronel J, Zimic M, Torok ME, Ayabina D, Kendall M, Fraser C, Harris S, Parkhill J, Peacock SJ, Moore DAJ, Colijn Cet al., 2017, Convergent evolution and topologically disruptive polymorphisms among multidrug-resistant tuberculosis in Peru, PLOS ONE, Vol: 12, ISSN: 1932-6203

JOURNAL ARTICLE

Jombart T, Kendall M, Almagro-Garcia J, Colijn Cet al., 2017, treespace: Statistical exploration of landscapes of phylogenetic trees, MOLECULAR ECOLOGY RESOURCES, Vol: 17, Pages: 1385-1392, ISSN: 1755-098X

JOURNAL ARTICLE

Ratmann O, Wymant C, Colijn C, Danaviah S, Essex M, Frost S, Gall A, Gaseitsiwe S, Grabowski MK, Gray R, Guindon S, von Haeseler A, Kaleebu P, Kendall M, Kozlov A, Manasa J, Minh BQ, Moyo S, Novitsky V, Nsubuga R, Pillay S, Quinn TC, Serwadda D, Ssemwanga D, Stamatakis A, Trifinopoulos J, Wawer M, Brown AL, de Oliveira T, Kellam P, Pillay D, Fraser Cet 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

JOURNAL ARTICLE

Sartelli M, Weber DG, Ruppe E, Bassetti M, Wright BJ, Ansaloni L, Catena F, Coccolini F, Abu-Zidan FM, Coimbra R, Moore EE, Moore FA, Maier RV, De Waele JJ, Kirkpatrick AW, Griffiths EA, Eckmann C, Brink AJ, Mazuski JE, May AK, Sawyer RG, Mertz D, Montravers P, Kumar A, Roberts JA, Vincent L, Watkins RR, Lowman W, Spellberg B, Abbott IJ, Adesunkanmi AK, Al-Dahir S, Al-Hasan MN, Agresta F, Althani AA, Ansari S, Ansumana R, Augustin G, Bala M, Balogh ZJ, Baraket O, Bhangu A, Beltrn MA, Bernhard M, Biffl WL, Boermeester MA, Brecher SM, Cherry-Bukowiec JR, Buyne OR, Cainzos MA, Cairns KA, Camacho-Ortiz A, Chandy SJ, Jusoh AC, Chichom-Mefire A, Colijn C, Corcione F, Cui Y, Curcio D, Delibegovic S, Demetrashvili Z, De Simone B, Dhingra S, Diaz JJ, Di Carlo I, Dillip A, Di Saverio S, Doyle MP, Dorj G, Dogjani A, Dupont H, Eachempati SR, Enani MA, Egiev VN, Elmangory MM, Ferrada P, Fitchett JR, Fraga GP, Guessennd N, Giamarellou H, Ghnnam W, Gkiokas G, Goldberg SR, Gomes CA, Gomi H, Guzman-Blanco M, Haque M, Hansen S, Hecker A, Heizmann WR, Herzog T, Hodonou AM, Hong SK, Kafka-Ritsch R, Kaplan LJ, Kapoor G, Karamarkovic A, Kees MG, Kenig J, Kiguba R, Kim PK, Kluger Y, Khokha V, Koike K, Kok KY, Kong V, Knox MC, Inaba K, Isik A, Iskandar K, Ivatury RR, Labbate M, Labricciosa FM, Laterre PF, Latifi R, Lee JG, Lee YR, Leone M, Leppaniemi A, Li Y, Liang SY, Loho T, Maegele M, Malama S, Marei HE, Martin-Loeches I, Marwah S, Massele A, McFarlane M, Melo RB, Negoi I, Nicolau DP, Nord CE, Ofori-Asenso R, Omari AH, Ordonez CA, Ouadii M, Pereira Junior GA, Piazza D, Pupelis G, Rawson TM, Rems M, Rizoli S, Rocha C, Sakakushev B, Sanchez-Garcia M, Sato N, Segovia Lohse HA, Sganga G, Siribumrungwong B, Shelat VG, Soreide K, Soto R, Talving P, Tilsed JV, Timsit JF, Trueba G, Trung NT, Ulrych J, Van Goor H, Vereczkei A, Vohra RS, Wani I, Uhl W, Xiao Y, Yuan KC, Zachariah SK, Zahar JR, Zakrison TL, Corcione A, Melotti RM, Viscoli C, Viale Pet 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

JOURNAL ARTICLE

Cobey S, Baskerville EB, Colijn C, Hanage W, Fraser C, Lipsitch Met 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

JOURNAL ARTICLE

Fyson N, King J, Belcher T, Preston A, Colijn Cet al., 2017, A curated genome-scale metabolic model of Bordetella pertussis metabolism, PLOS COMPUTATIONAL BIOLOGY, Vol: 13, ISSN: 1553-734X

JOURNAL ARTICLE

Klinkenberg D, Backer JA, Didelot X, Colijn C, Wallinga Jet al., 2017, Simultaneous inference of phylogenetic and transmission trees in infectious disease outbreaks, PLOS COMPUTATIONAL BIOLOGY, Vol: 13, ISSN: 1553-734X

JOURNAL ARTICLE

Didelot X, Fraser C, Gardy J, Colijn Cet al., 2017, Genomic Infectious Disease Epidemiology in Partially Sampled and Ongoing Outbreaks, MOLECULAR BIOLOGY AND EVOLUTION, Vol: 34, Pages: 997-1007, ISSN: 0737-4038

JOURNAL ARTICLE

Colijn C, Jones N, Johnston IG, Yaliraki S, Barahona Met al., 2017, Toward Precision Healthcare: Context and Mathematical Challenges, FRONTIERS IN PHYSIOLOGY, Vol: 8, ISSN: 1664-042X

JOURNAL ARTICLE

Ratmann O, Hodcroft EB, Pickles M, Cori A, Hall M, Lycett S, Colijn C, Dearlove B, Didelot X, Frost S, Hossain ASMM, Joy JB, Kendall M, Kuhnert D, Leventhal GE, Liang R, Plazzotta G, Poon AFY, Rasmussen DA, Stadler T, Volz E, Weis C, Brown AJL, Fraser Cet 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

JOURNAL ARTICLE

Plazzotta G, Colijn C, 2016, ASYMPTOTIC FREQUENCY OF SHAPES IN SUPERCRITICAL BRANCHING TREES, Publisher: CAMBRIDGE UNIV PRESS

WORKING PAPER

Ayabina D, Hendon-Dunn C, Bacon J, Colijn Cet 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

JOURNAL ARTICLE

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

JOURNAL ARTICLE

Sartelli M, Weber DG, Ruppe E, Bassetti M, Wright BJ, Ansaloni L, Catena F, Coccolini F, Abu-Zidan FM, Coimbra R, Moore EE, Moore FA, Maier RV, De Waele JJ, Kirkpatrick AW, Griffiths EA, Eckmann C, Brink AJ, Mazuski JE, May AK, Sawyer RG, Mertz D, Montravers P, Kumar A, Roberts JA, Vincent J-L, Watkins RR, Lowman W, Spellberg B, Abbott IJ, Adesunkanmi AK, Al-Dahir S, Al-Hasan MN, Agresta F, Althani AA, Ansari S, Ansumana R, Augustin G, Bala M, Balogh ZJ, Baraket O, Bhangu A, Beltran MA, Bernhard M, Biffl WL, Boermeester MA, Brecher SM, Cherry-Bukowiec JR, Buyne OR, Cainzos MA, Cairns KA, Camacho-Ortiz A, Chandy SJ, Jusoh AC, Chichom-Mefire A, Colijn C, Corcione F, Cui Y, Curcio D, Delibegovic S, Demetrashvili Z, De Simone B, Dhingra S, Diaz JJ, Di Carlo I, Dillip A, Di Saverio S, Doyle MP, Dorj G, Dogjani A, Dupont H, Eachempati SR, Enani MA, Egiev VN, Elmangory MM, Ferrada P, Fitchett JR, Fraga GP, Guessennd N, Giamarellou H, Ghnnam W, Gkiokas G, Goldberg SR, Gomes CA, Gomi H, Guzman-Blanco M, Haque M, Hansen S, Hecker A, Heizmann WR, Herzog T, Hodonou AM, Hong S-K, Kafka-Ritsch R, Kaplan LJ, Kapoor G, Karamarkovic A, Kees MG, Kenig J, Kiguba R, Kim PK, Kluger Y, Khokha V, Koike K, Kok KYY, Kong V, Knox MC, Inaba K, Isik A, Iskandar K, Ivatury RR, Labbate M, Labricciosa FM, Laterre P-F, Latifi R, Lee JG, Lee YR, Leone M, Leppaniemi A, Li Y, Liang SY, Loho T, Maegele M, Malama S, Marei HE, Martin-Loeches I, Marwah S, Massele A, McFarlane M, Melo RB, Negoi I, Nicolau DP, Nord CE, Ofori-Asenso R, Omari AH, Ordonez CA, Ouadii M, Pereira Junior GA, Piazza D, Pupelis G, Rawson TM, Rems M, Rizoli S, Rocha C, Sakakhushev B, Sanchez-Garcia M, Sato N, Lohse HAS, Sganga G, Siribumrungwong B, Shelat VG, Soreide K, Soto R, Talving P, Tilsed JV, Timsit J-F, Trueba G, Trung NT, Ulrych J, van Goor H, Vereczkei A, Vohra RS, Wani I, Uhl W, Xiao Y, Yuan K-C, Zachariah SK, Zahar J-R, Zakrison TL, Corcione A, Melotti RM, Viscoli C, Viale Pet 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

JOURNAL ARTICLE

Aanensen DM, Feil EJ, Holden MTG, Dordel J, Yeats CA, Fedosejev A, Goater R, Castillo-Ramirez S, Corander J, Colijn C, Chlebowicz MA, Schouls L, Heck M, Pluister G, Ruimy R, Kahlmeter G, Ahman J, Matuschek E, Friedrich AW, Parkhill J, Bentley SD, Spratt BG, Grundmann Het 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

JOURNAL ARTICLE

Hatherell H-A, Didelot X, Pollock SL, Tang P, Crisan A, Johnston JC, Colijn C, Gardy JLet al., 2016, Declaring a tuberculosis outbreak over with genomic epidemiology, MICROBIAL GENOMICS, Vol: 2, ISSN: 2057-5858

JOURNAL ARTICLE

Kendall ML, Boyd M, Colijn C, 2016, phyloTop

Tools for calculating and viewing topological properties of phylogenetic trees.

SOFTWARE

Hatherell H-A, Colijn C, Stagg HR, Jackson C, Winter JR, Abubakar Iet al., 2016, Interpreting whole genome sequencing for investigating tuberculosis transmission: a systematic review, BMC MEDICINE, Vol: 14, ISSN: 1741-7015

JOURNAL ARTICLE

Plazzotta G, Kwan C, Boyd M, Colijn Cet al., 2016, Effects of memory on the shapes of simple outbreak trees, SCIENTIFIC REPORTS, Vol: 6, ISSN: 2045-2322

JOURNAL ARTICLE

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