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Ancestral population genomics using coalescence hidden Markov models and heuristic optimisation algorithms

Jade Yu Cheng, Thomas Mailund
2015 Computational biology and chemistry  
In this paper we present a framework for building such coalescence hidden Markov models for pairwise alignments and present results for using heuristic optimisation algorithms for parameter estimation.  ...  Conclusions and future work We have described a new framework for constructing coalescence hidden Markov models for demographic inference and showed that using heuristic optimisation algorithms we can  ...  JC implemented the optimisation algorithms. Both authors designed the experiments and analysed the results. JC executed the experiments. Both authors drafted the manuscript.  ... 
doi:10.1016/j.compbiolchem.2015.02.001 pmid:25819138 fatcat:tptoowikhbgptkfotbvygepsim

Towards more realistic models of genomes in populations: the Markov-modulated sequentially Markov coalescent [article]

Julien Y. Dutheil
2020 arXiv   pre-print
The sequentially Markov coalescent (SMC) is a heuristic that enables the modelling of complete genomes under the coalescent framework.  ...  In the genomic era, however, coalescent models are limited due to the complexity of the underlying ancestral recombination graph.  ...  Spence and an anonymous reviewer for their careful reading of the manuscript, for finding several mistakes and typos, and for their suggestions on how to improve its clarity.  ... 
arXiv:2010.08359v1 fatcat:a63e2kkpgzeylg255354l2kiim

Populations in statistical genetic modelling and inference [article]

Daniel John Lawson
2013 arXiv   pre-print
We discuss generative models using drift, admixture and spatial structure, and the ancestral recombination graph.  ...  We conclude that populations are a useful theoretical construct that can be well defined in theory and often approximately exist in practice.  ...  Hidden Markov Model: A Hidden Markov Model is a statistical model decomposing the probability of the data x i at locations i into two parts using a set of hidden variables y i .  ... 
arXiv:1306.0701v1 fatcat:xii46ijgj5hmjig2lo4sdk5zsi

Populations in Statistical Genetic Modelling and Inference [chapter]

Daniel John Lawson
2015 Population in the Human Sciences  
Please cite only the published version using the reference above. Full terms of use are available:  ...  in a 'tree-building' 12 step, using a heuristic model for kinship.  ...  The model takes a computationally convenient form called a Hidden Markov Model 8 , which allows for a fast inference of a wide range of useful summaries with complete accounting for statistical uncertainty  ... 
doi:10.1093/acprof:oso/9780199688203.003.0004 fatcat:drgokfcrefeidjb6onoddw7ogq

Robust Design for Coalescent Model Inference [article]

Kris V Parag, Oliver G Pybus
2018 bioRxiv   pre-print
We examine three key design problems: temporal sampling of sequences under the skyline demographic coalescent model, spatio-temporal sampling for the structured coalescent model, and time discretisation  ...  for sequentially Markovian coalescent models.  ...  These methods typically handle SMC inference by constructing a hidden Markov model (HMM) over discretised coalescent time [10] [41] [11] .  ... 
doi:10.1101/317438 fatcat:5wknif4frvc4fhow5jmgeivxqe

Identity-by-descent detection across 487,409 British samples reveals fine-scale population structure, evolutionary history, and trait associations [article]

Juba Nait Saada, Georgios Kalantzis, Derek Shyr, Martin Robinson, Alexander Gusev, Pier Francesco Palamara
2020 bioRxiv   pre-print
These results underscore the importance of modelling distant relatedness to reveal subtle population structure, recent evolutionary history, and rare pathogenic variation.  ...  FastSMC combines a fast heuristic search for IBD segments with accurate coalescent-based likelihood calculations and enables estimating the age of common ancestors transmitting IBD regions.  ...  Genomic relationships and speciation times 540 of human, chimpanzee, and gorilla inferred from a coalescent hidden markov model. PLoS genetics, 3(2):e7, 2007. 541 69. KL Simonsen and Gary Churchill.  ... 
doi:10.1101/2020.04.20.029819 fatcat:mbvyv54eyzfvtapzi32s6ozsle

A cautionary note on the use of unsupervised machine learning algorithms to characterise malaria parasite population structure from genetic distance matrices

James A. Watson, Aimee R. Taylor, Elizabeth A. Ashley, Arjen Dondorp, Caroline O. Buckee, Nicholas J. White, Chris C. Holmes, Giorgio Sirugo
2020 PLoS Genetics  
We illustrate the sensitivity of PCoA and HAC using 393 Plasmodium falciparum whole genome sequences collected from Cambodia and neighbouring regions (where antimalarial resistance has emerged and spread  ...  To bridge the inferential disconnect between the output of non-inferential unsupervised learning algorithms and the scientific questions of interest, tailor-made statistical models are needed to infer  ...  Acknowledgments We thank Dominic Kwiatkowski for suggesting improvements to the manuscript and for pointing out the relevance of the Relate program. We thank Sungsik Kong and Santiago J.  ... 
doi:10.1371/journal.pgen.1009037 pmid:33035220 fatcat:s3mt77thfnhdzmnl5o4gkwr4yy

A cautionary note on the use of machine learning algorithms to characterise malaria parasite population structure from genetic distance matrices [article]

James A Watson, Aimee R Taylor, Elizabeth A Ashley, Arjen Dondorp, Caroline O Buckee, Nicholas J White, Chris C Holmes
2020 bioRxiv   pre-print
We illustrate the sensitivity of PCoA and HAC using 393 P. falciparum whole genome sequences collected from Cambodia and neighbouring regions (where antimalarial resistance has emerged and spread recently  ...  Many of the methods used to characterise structure are algorithms developed in machine learning (ML) and depend on a genetic distance matrix, e.g. principal coordinates analysis (PCoA) and hierarchical  ...  We thank Sungsik Kong and Santiago 674 J. Sánchez-Pacheco for helpful comments on the first preprint version of the manuscript. 675  ... 
doi:10.1101/2020.03.23.004598 fatcat:sgkrpb4jgzhtbjao6r7ojzdjd4

44th European Mathematical Genetics Meeting (EMGM) 2016. Newcastle upon Tyne, UK, May 11-12, 2016: Abstracts

2015 Human Heredity  
We first introduce a breakpoint model for logistic regression which purpose is to estimate both regression coefficients and breakpoint locations using a constrained hidden Markov model (HMM) and a generalized  ...  Then we show how this model can be used to detect unaccounted heterogeneity in GWAS using a likelihood ratio test. Our breakpoint model and the new GxE test are first validated on simple simulations.  ...  This performance was then contrasted with models using the traditional single PRS across the whole genome.  ... 
doi:10.1159/000445228 pmid:27111916 fatcat:553k64equ5f7lkbhpwun7nbgkm

Molecular evolution of biological sequences

Ignacio Vázquez García, Apollo-University Of Cambridge Repository, Apollo-University Of Cambridge Repository, Ville Mustonen
2018
This method uses Hidden Markov Models for the deconvolution of genetically diverse populations and can be applied to clonal admixtures of genomes in any asexual population, from evolving pathogens to the  ...  We then present a probabilistic model to reconstruct genotypically distinct lineages in mixed cell populations from DNA sequencing.  ...  We introduce Hidden Markov Models (HMMs) and show how they can be used to model sequences of a mixed population of related cells.  ... 
doi:10.17863/cam.31541 fatcat:l45pdonp2vf6njbwyp6kedouia

A sequential Monte Carlo algorithm with transformations for Bayesian model exploration: applications in population genetics

Richard James Culliford
2019
We test these strengths of tSMC under three applications, which include two population genetics applications being ancestral reconstruction under the coalescent and the other being the Structure algorithm  ...  the number of discrete values, but using a lower dimensional model and incorporating it into the model exploration assists with convergence.  ...  The first coalescent event occurs at x 4 = 0.3 between individual genomes y 3 and y 4 .  ... 
doi:10.48683/1926.00084849 fatcat:qzhpc4tq5ngofawvl4m74h5uci

2014 Centre for eResearch Annual Report [article]

Jenny Lee Roper, Mark Gahegan
2018
We passed the landmark of 50 million CPU hours delivered and used by researchers since our record keeping began in January 2012.Over 50 scholars have now passed the mark of using over 500,000 CPU hours  ...  We now provide a Research Virtual Machine (RVM) service that supports interactive research applications, both on Linux and Windows, we also run a large-scale visualisation facility (using 20 displays working  ...  We'd also like to thank the New Zealand eScience Infrastructure (NeSI) for providing High Performance Computing platforms, data services and the computational support team.  ... 
doi:10.17608/k6.auckland.6174224 fatcat:z73vjuee7vfvvbihxislxn5dna

Scalable Tools for High-throughput Viral Sequence Analysis

A S Md Mukarram Hossain, Apollo-University Of Cambridge Repository, Apollo-University Of Cambridge Repository, Simon Frost
2018
Viral sequence data are increasingly being used to estimate evolutionary and epidemiological parameters to understand the dynamics of viral diseases.  ...  ANVIL's performance was benchmarked using two large HIV datasets collected from the Los Alamos HIV Sequence Database and the UK HIV Drug Resistance Database, as well as on simulated data.  ...  From the department of Veterinary Medicine, I would like to acknowledge the Disease Dynamics Unit and the Laboratory of Viral Zoonotics for the useful presentations, discussions, comments and encouragement  ... 
doi:10.17863/cam.23510 fatcat:bd5lukkfwbhlzmd5rxuno5q2d4

50th European Mathematical Genetics Meeting (EMGM) 2022

2022
Previous theoretical models proceeded from the  ...  We investigate the underlying parameters of PSMC's hidden Markov model and show that the transition matrix contains information that can reveal the presence of ancestral population structure.  ...  We developed a statistical algorithm called FoundHaplo, which is a hidden Markov model designed to identify individuals with inherited disease-causing genetic variants using SNP data.  ... 
doi:10.1159/000524615 pmid:35443248 fatcat:teoklss77zg7fkvnqrimm6ez3e

Phylogenetics, Phylogeography and the Evolutionary History of the Chestnut-Shouldered Group of Fairy-Wrens (Malurus spp.)

Alison McLean, University, My, Jane Hughes
2018
), five anonymous nuclear loci and three nuclear introns.  ...  In the first data chapter of this thesis, I reconstructed the phylogeny of all four species of chestnut-shouldered fairy-wrens including all four subspecies of M. lamberti using a mitochondrial gene (ND2  ...  Doyle 1987) was used to isolate total genomic DNA.  ... 
doi:10.25904/1912/2448 fatcat:qpvi6cgu3fb7djl6fky5jtzdre
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