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Relevant bibliographies by topics / Ancestral recombination graphs

Academic literature on the topic 'Ancestral recombination graphs'

Author: Grafiati

Published: 9 March 2023

Last updated: 10 March 2023

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Journal articles on the topic "Ancestral recombination graphs"

1

Song, Yun S., and Jotun Hein. "Constructing Minimal Ancestral Recombination Graphs." Journal of Computational Biology 12, no. 2 (March 2005): 147–69. http://dx.doi.org/10.1089/cmb.2005.12.147.

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Mahmoudi, Ali, Jere Koskela, Jerome Kelleher, Yao-ban Chan, and David Balding. "Bayesian inference of ancestral recombination graphs." PLOS Computational Biology 18, no. 3 (March 9, 2022): e1009960. http://dx.doi.org/10.1371/journal.pcbi.1009960.

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We present a novel algorithm, implemented in the software ARGinfer, for probabilistic inference of the Ancestral Recombination Graph under the Coalescent with Recombination. Our Markov Chain Monte Carlo algorithm takes advantage of the Succinct Tree Sequence data structure that has allowed great advances in simulation and point estimation, but not yet probabilistic inference. Unlike previous methods, which employ the Sequentially Markov Coalescent approximation, ARGinfer uses the Coalescent with Recombination, allowing more accurate inference of key evolutionary parameters. We show using simulations that ARGinfer can accurately estimate many properties of the evolutionary history of the sample, including the topology and branch lengths of the genealogical tree at each sequence site, and the times and locations of mutation and recombination events. ARGinfer approximates posterior probability distributions for these and other quantities, providing interpretable assessments of uncertainty that we show to be well calibrated. ARGinfer is currently limited to tens of DNA sequences of several hundreds of kilobases, but has scope for further computational improvements to increase its applicability.

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Kuhner, Mary K., and Jon Yamato. "Assessing Differences Between Ancestral Recombination Graphs." Journal of Molecular Evolution 80, no. 5-6 (April 5, 2015): 258–64. http://dx.doi.org/10.1007/s00239-015-9676-x.

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Rasmussen, Matthew D., Melissa J. Hubisz, Ilan Gronau, and Adam Siepel. "Genome-Wide Inference of Ancestral Recombination Graphs." PLoS Genetics 10, no. 5 (May 15, 2014): e1004342. http://dx.doi.org/10.1371/journal.pgen.1004342.

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Nguyen, Thao Thi Phuong, Vinh Sy Le, Hai Bich Ho, and Quang Si Le. "Building Ancestral Recombination Graphs for Whole Genomes." IEEE/ACM Transactions on Computational Biology and Bioinformatics 14, no. 2 (March 1, 2017): 478–83. http://dx.doi.org/10.1109/tcbb.2016.2542801.

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Kuhner, Mary K., and Jon Yamato. "A Consensus Method for Ancestral Recombination Graphs." Journal of Molecular Evolution 84, no. 2-3 (March 2017): 129–38. http://dx.doi.org/10.1007/s00239-017-9786-8.

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Vaughan, Timothy G., David Welch, Alexei J. Drummond, Patrick J. Biggs, Tessy George, and Nigel P. French. "Inferring Ancestral Recombination Graphs from Bacterial Genomic Data." Genetics 205, no. 2 (December 22, 2016): 857–70. http://dx.doi.org/10.1534/genetics.116.193425.

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Deng, Yun, Yun S. Song, and Rasmus Nielsen. "The distribution of waiting distances in ancestral recombination graphs." Theoretical Population Biology 141 (October 2021): 34–43. http://dx.doi.org/10.1016/j.tpb.2021.06.003.

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Heine, K., A. Beskos, A. Jasra, D. Balding, and M. De Iorio. "Bridging trees for posterior inference on ancestral recombination graphs." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 474, no. 2220 (December 2018): 20180568. http://dx.doi.org/10.1098/rspa.2018.0568.

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We present a new Markov chain Monte Carlo algorithm, implemented in the software Arbores, for inferring the history of a sample of DNA sequences. Our principal innovation is a bridging procedure, previously applied only for simple stochastic processes, in which the local computations within a bridge can proceed independently of the rest of the DNA sequence, facilitating large-scale parallelization.

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Yang, Shuo, Shai Carmi, and Itsik Pe'er. "Rapidly Registering Identity-by-Descent Across Ancestral Recombination Graphs." Journal of Computational Biology 23, no. 6 (June 2016): 495–507. http://dx.doi.org/10.1089/cmb.2016.0016.

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Dissertations / Theses on the topic "Ancestral recombination graphs"

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Minichiello, Mark Joseph. "Analysis of genetic variation data using ancestral recombination graphs." Thesis, University of Cambridge, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.613255.

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CARRIERI, ANNA PAOLA. "Sampling Ancestral Recombination Graphs and Reconstruction of Phylogenetic Trees for Explaining Evolution." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2016. http://hdl.handle.net/10281/102072.

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The aim of the thesis is the development of algorithms to study the evolution of genomic information starting from data produced by Next Generation Sequencing (NGS) technologies. We address the problem of reconstructing evolutionary histories following two research directions which both explore algorithms for the generation (or reconstruction) of ancestral recombination graphs (or phylogenetic trees) modeling the evolution in presence of evolutionary events, such as recombination and Single Nucleotide Polymorphisms (SNPs). The first research direction regards the development of efficient algorithms for simulating complex scenarios of multiple population evolution with admixture. The aim of simulations is to obtain the resulting extant population samples and their common relevant evolutionary history captured by an ARG. We propose a backward simulation algorithm, named SimRA, for modeling complex evolutionary scenarios, which improves time and space requirements of the classical algorithm of single populations. Through extensive simulation experiments, we show that SimRA produces ARGs in compact form without compromising any accuracy. Moreover, we present the first combinatorial approach, based on persistency in topology, which detects admixture in populations. We show, based on efficient and controlled simulations computed by SimRA, that the topological framework has the potential for detecting admixture in related populations. The second research direction regards the development of efficient algorithms to reconstruct phylogenesis of contemporary species described by genomic binary characters. Established maximum parsimony models are Dollo and Camin-Sokal, both leading to NP-hard reconstruction problems. On the other hand, the perfect phylogeny, which has very efficient polynomial time algorithmic solutions, is often too restrictive for explaining the evolution of real biological data where homoplasy is present. We address the problem of reconstructing a variant of the perfect phylogeny model, the persistent phylogeny, that is more widely applicable, with the aim of retaining the computational efficiency. For this purpose, we introduce the Constrained Persistent Perfect Phylogeny problem (CPPP) which generalizes the Persistent Perfect Phylogeny (PPP) problem, by adding constraints for some observed characters. We provide a polynomial time algorithm for a particular class of instances and a parameterized algorithm for solving the general problem. We conclude the thesis with results concerning the scaffold filling computational problem which derives from the necessity of filling incomplete genomic sequences in order to maximize their similarity with a known reference genome. We consider two scaffold filling problems (One-sided and Two-sided) that are NP-hard under the maximum number of common adjacencies similarity. We design two Fixed Parameterized Tractable (FPT)-algorithms respectively for the One-side and Two-side scaffold filling problem, with only one parameter representing the number of common adjacencies between the two filled genomes.

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Miró, Pina Verónica. "Equilibrium patterns of genetic diversity shuffled by migration and recombination." Thesis, Sorbonne université, 2018. http://www.theses.fr/2018SORUS253.

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Cette thèse présente deux modèles différents pour étudier comment la recombinaison et la migration permettent de brasser la diversité génétique. Dans le premier modèle, au temps 0, chaque individu a son chromosome peint d’une couleur différente. Par l’effet de la recombinaison, les génomes des descendants sont des mosaïques de couleurs, où chaque couleur représente le matériel génétique hérité d’un des ancêtres. Chaque segment d’une même couleur correspond à un segment identique par descendance (IBD en anglais). Nous avons caractérisé la distribution des blocks IBD dans le chromosome d’un individu échantillonné au hasard dans la population. Le deuxième modèle permet d’étudier l’effet de la structure géographique, la migration, la mutation et la recombinaison sur la composition génétique d’une métapopulation. La métapopulation est représentée par un graphe où chaque sommet représente une sous-population et chaque arrête est associée à un taux de migration. Le but est d’étudier la spéciation: quand deux sous-populations accumulent assez de différences génétiques, elles peuvent former deux espèces séparées. Nous avons caractérisé la distribution des distances génétiques entre les sous-populations dans un régime de mutation et migration rares, en fonction de la structure géographique. Nous avons montré que certaines structures géographiques peuvent favoriser la spéciation
This thesis presents two different models to study how recombination and migration shuffle genetic diversity. In the first model, recombination is the only evolutionary force. At time 0, each individual has her unique chromosome painted in a distinct color. By the blending effect of recombination, the genomes of the descending individuals look like mosaics of colors, each color representing the genetic material inherited from a different ancestral individual. Each segment of the same color is called an identical-by-descent (IBD) segment. We have been able to characterize the sizes and positions of the segments that are IBD to a given locus in the chromosome of a randomly sampled individual in the population. The second model is devoted to the study of the effects of geographic structure, migration, mutation and recombination in the genetic composition of a metapopulation. The metapopulation is modelled as a graph where vertices correspond to subpopulations and edges are associated to migration rates. The idea behind this project is to study speciation: when two subpopulations accumulate enough genetic differences they may become separate species. We have been able to characterize the distribution of the genetic distances between subpopulations in a low mutation - low migration regime, depending on the geographic structure, and to show that some geographic configurations can promote speciation

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Melé, Messeguer Marta. "Incorporating recombination into the study of recent human evolutionary history." Doctoral thesis, Universitat Pompeu Fabra, 2011. http://hdl.handle.net/10803/22684.

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En aquest treball es pretén utilitzar la informació que deixa la recombinació al nostres genomes per fer inferències sobre la història evolutiva recent de les poblacions humanes. Per fer-ho, s’ha desenvolupat un mètode novedós, anomenat IRiS, que permet la detecció de recombinacions antigues específiques en un conjunt de seqüències. Hem validat extensivament IRiS i l'hem sotmès a diferents escenaris per tal d’avaluar-ne l’ eficàcia. Un cop els events de recombinació són detectats, es poden utilitzar com a marcadors genètics per estudiar els patrons de diversitat de les poblacions humanes. Finalment, hem aplicat aquesta innovadora aproximació a un conjunt de poblacions humanes del Vell Món, que varen ser genotipades específicament amb aquesta finalitat, aportant nous coneixements en la història evolutiva recent dels humans
The aim of this work is to use the information left by recombination in our genomes to make inferences on the recent evolutionary history of human populations. For that, a novel method called IRiS has been developed that allows detecting specific past recombination events in a set of extant sequences. IRiS is extensively validated and studied in whole set of different scenarios in order to assess its performance. Once recombination events are detected, they can be used as genetic markers to study the recombinational diversity patterns of human populations. We apply this innovative approach to a whole set of different human populations within the Old World that were specifically genotyped for this end and we provide new insights in the recent human evolutionary history of our species.

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Salamat, Majid. "Coalescent, recombinaisons et mutations." Thesis, Aix-Marseille 1, 2011. http://www.theses.fr/2011AIX10059.

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Cette thèse se concentre sur certains sujets en génétique des populations. Dans la première partie, nous donnons des formules y compris l'espérance et la variance de la hauteur et celles de la longueur du graphe de recombinaison ancestral (ARG) et l'espérance et la variance du nombre de recombinaison et nous montrons que l'espérance de la longueur de l'ARG est une combinaison linéaire de l'espérance de la longueur de la coalescence de Kingman et l'espérance de la hauteur de l'ARG. En outre, nous avons obtenu une relation entre l'espérance la longueur de l'ARG et l'espérance du nombre de recombinaisons. À la fin de cette partie, nous montrons que l'ARG descend de l'infini de telle sorte que X_0 =∞, alors que X_t < ∞ ; pour tout t et on trouve la vitesse à laquelle l'ARG descend de l'infini. Dans la deuxième partie on généralise la formule d'échantillonnage d'Ewens (GESF) en présence de la recombinaison pour les échantillons de taille n = 2 et n = 3. Dans la troisième partie de la thèse, nous étudions l'ARG le long du génome et nous avons trouvé la distribution du nombre de mutations dans le cas avec une seule recombinaison dans la généalogie de l'échantillon
This thesis is concentrated on some sub jects on population genetics. In the first part we give formulae including the expectation and variance of the height and the length of the ancestral recombination graph (ARG) and the expectation and variance of the number of recombination events and we show that the expectation of the length of the ARG is a linear combination of the expectation of the length of Kingman's coalescent and the expectation of the height of the ARG. Also we show give a relation between the expectation of the ARG and the expectation of the number of recombination events. At the end of this part we show that the ARG comes down from infinity in the sense that we can dfine it with X_0 = ∞, while X_t <∞ ; for all t and we find the speed that the ARG comes down from infinity. In the second part wfind a generalization of the the Ewens sampling formula (GESF) in the presence of recombination for sample of sizes n = 2 and n = 3. In the third part of the thesis we study the ARG along the genome and we we find the distribution of the number of mutations when we have one recombination event in the genealogy of the sample

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Books on the topic "Ancestral recombination graphs"

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Gusfield, Dan. ReCombinatorics: The Algorithmics of Ancestral Recombination Graphs and Explicit Phylogenetic Networks. MIT Press, 2014.

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Gusfield, Dan. ReCombinatorics: The Algorithmics of Ancestral Recombination Graphs and Explicit Phylogenetic Networks. MIT Press, 2014.

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Gusfield, Dan. ReCombinatorics: The Algorithmics of Ancestral Recombination Graphs and Explicit Phylogenetic Networks. The MIT Press, 2014.

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Gusfield, Dan. ReCombinatorics: The Algorithmics of Ancestral Recombination Graphs and Explicit Phylogenetic Networks. MIT Press, 2014.

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Book chapters on the topic "Ancestral recombination graphs"

1

Hubisz, Melissa, and Adam Siepel. "Inference of Ancestral Recombination Graphs Using ARGweaver." In Methods in Molecular Biology, 231–66. New York, NY: Springer US, 2020. http://dx.doi.org/10.1007/978-1-0716-0199-0_10.

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Yang, Shuo, Shai Carmi, and Itsik Pe’er. "Rapidly Registering Identity-by-Descent Across Ancestral Recombination Graphs." In Lecture Notes in Computer Science, 340–53. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16706-0_35.

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Griffiths, Robert C., and Paul Marjoram. "An Ancestral Recombination Graph." In Progress in Population Genetics and Human Evolution, 257–70. New York, NY: Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4757-2609-1_16.

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Parida, Laxmi. "Nonredundant Representation of Ancestral Recombinations Graphs." In Methods in Molecular Biology, 315–32. Totowa, NJ: Humana Press, 2012. http://dx.doi.org/10.1007/978-1-61779-585-5_13.

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Pritchard, Jonathan, and Sebastian Zöllner. "Use of a Local Approximation to the Ancestral Recombination Graph for Fine Mapping Disease Genes." In Computational Methods for SNPs and Haplotype Inference, 141. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24719-7_21.

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Conference papers on the topic "Ancestral recombination graphs"

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Phuong Thao, Nguyen Thi, and Le Sy Vinh. "Building minimum recombination ancestral recombination graphs for whole genomes." In 2017 4th NAFOSTED Conference on Information and Computer Science. IEEE, 2017. http://dx.doi.org/10.1109/nafosted.2017.8108072.

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Thao, Nguyen Thi Phuong, and Le Sy Vinh. "A Hybrid Approach to Optimize the Number of Recombinations in Ancestral Recombination Graphs." In the 2019 9th International Conference. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3314367.3314385.

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