ライフサイエンスコーパス: coalescent

1 ILS), which is modelled by the multi-species coalescent.

2 ference on these data under the multispecies coalescent.

3 data from an island model using the neutral coalescent.

4 led genetic structure under the multispecies coalescent.

5 or exploiting the inherent symmetries of the coalescent.

6 well as its accuracy under the multispecies coalescent.

7 Here, we study the accuracy of the coalescent, a central model for studying the ancestry of

8 In multispecies coalescent, a gene tree topology is observed with some p

9 th built on fast, modified sequential Markov coalescent algorithms to approximate standard coalescent

10 his work, we extend the sequential Markovian coalescent, an approximation to the coalescent with reco

11 Coalescent analyses indicate that P. filamentosus may ha

12 Bayesian coalescent analyses indicated that this variant arose in

13 Bayesian coalescent analyses of available whole S, M, and L segme

14 We combined our own Bayesian coalescent analyses of VP1 regions from four picornaviru

15 23, which had an origin in 1908 as dated by coalescent analysis and included isolates with a diverge

16 e, cross-platform and scalable framework for coalescent analysis in population genetics.

17 t spots in plants, which lack PRDM9, we used coalescent analysis of genetic variation in Arabidopsis

18 n this procedure and develop corrections for coalescent analysis of SNPs obtained via a panel.

19 re to be commended for attempting to use the coalescent analysis of viral sequence data to evaluate a

20 We provide several examples illustrating how coalescent analysis provides critical insights into unde

21 Coalescent analysis revealed that although the genetic d

22 Coalescent analysis shows that the Khoisan and their anc

23 lation-migration model was evaluated using a coalescent analysis to estimate multiple demographic par

24 m a time window of 1977-2012, were used in a coalescent analysis with BEAST software to estimate the

25 Bayesian evolutionary analysis (coalescent analysis) based on genetic sequences has been

26 tion for the domain of exact calculations in coalescent analysis.

27 ed through comparative genomics and Bayesian coalescent analysis.

28 The ARG determines both the sequence of coalescent ancestries across the chromosome and the exta

29 We used coalescent and assignment methods to investigate the tim

30 the simplistic assumptions of commonly used coalescent and birth-death process models.

31 on the expected frequency spectrum under the coalescent and by leveraging the technique of automatic

32 nt tree (LCT), that simultaneously describes coalescent and duplication-loss history.

33 Here, we present results from coalescent and forward simulations designed to evaluate

34 ractional volume delivery based on partially coalescent and noncoalescent droplet collisions as a new

35 ngle diploid samples generated with standard coalescent and recombination models.

36 expected number of rare variants between the coalescent and the DTWF model.

37 y the differences between the fixed-pedigree coalescent and the standard coalescent by analysis and s

38 netic analyses implementing the multispecies coalescent and using previously published phylogenetic s

39 However, the popular full hierarchical coalescent approach implemented in *BEAST provided incon

40 applied the pairwise sequentially Markovian coalescent approach on the genomes of 11 temperate Jugla

41 es we employed a recently developed Bayesian coalescent approach to globally sampled human and avian

42 We propose a coalescent approach to search for SNPs associated with q

43 Using a Bayesian coalescent approach, we infer the evolutionary and epide

44 is using both concatenation and multispecies coalescent approaches (ASTRAL-II and SVDquartets).

45 f rabies persistence and validate the use of coalescent approaches for uncovering even relatively com

46 oalescent algorithms to approximate standard coalescent, are much more efficient whilst keeping salie

47 The coalescent arises as a limit of a large class of random

48 ve population size (Ne ) and used a Bayesian-coalescent based approach that simultaneously considers

49 The coalescent-based analysis revealed strong evidence for d

50 We used a Bayesian, coalescent-based approach to obtain information about an

51 Coalescent-based approaches are promising for LD mapping

52 uggest a new genealogy-based approach, CAMP (coalescent-based association mapping), that takes into a

53 we use it to produce the first genome-scale coalescent-based avian tree of life.

54 Here, we describe a coalescent-based full-likelihood Markov chain Monte Carl

55 Here we integrate coalescent-based genetic models [3, 4] with ecological-n

56 Recently, Li and Durbin developed a coalescent-based hidden Markov model, called the pairwis

57 The success of this approach has lead to coalescent-based inference methods being applied to popu

58 Coalescent-based inference required fewer sampled indivi

59 We introduce a coalescent-based method (RECOAL) for the simulation of n

60 Here, we present a new coalescent-based method that can efficiently infer popul

61 g improves the accuracy of MP-EST, a popular coalescent-based method, and we use it to produce the fi

62 We recently developed a coalescent-based method, ASTRAL, which is statistically

63 Another coalescent-based method, nested clade phylogeographic an

64 Using a full maximum-likelihood coalescent-based method, the ratio of the recombination

65 es tree from these trees using the preferred coalescent-based method.

66 model and which is more accurate than other coalescent-based methods on the datasets we examined.

67 BUCKy, two statistically consistent leading coalescent-based methods.

68 We then use coalescent-based modeling techniques to identify the evo

69 At the same time, the coalescent-based models of the pathogen population that

70 thods which maximize either likelihood under coalescent-based models or pseudo-likelihood approximati

71 vallavatn relative to historically explicit, coalescent-based null models of the evolutionary history

72 this approach by developing a retrospective coalescent-based serial founder model that incorporates

73 ransferability, we developed a complex trait coalescent-based simulation framework considering effect

74 Coalescent-based simulation software for genomic sequenc

75 quences from NGS data, we produced the first coalescent-based species tree estimate for CBSV and UCBS

76 Although coalescent-based species tree estimation methods can hav

77 New analytical methods based on coalescent, Bayesian and likelihood approaches permit mo

78 conversion: the bacterial sequential Markov coalescent (BSMC).

79 e fixed-pedigree coalescent and the standard coalescent by analysis and simulations.

80 nder the DTWF model, which are absent in the coalescent by construction.

81 a simple model of random evolution where the coalescent corresponded to the T/F sequence.

82 We show that the multispecies coalescent diagnoses genetic structure, not species, and

83 is an approximation to the full recombinant-coalescent distribution.

84 using Kingman's standard coalescent, with a coalescent effective population size 4N.

85 Third, even if the coalescent effective population size does not exist in t

86 Second, the requirement that the coalescent effective population size must depend linearl

87 Estimates of the coalescent effective population size N(e) can be poorly

88 We suggest two extensions of the coalescent effective population size of Sjodin et al. an

89 le variation in other traits that affect the coalescent effective population size, such as sex ratio

90 rences in regulation, evolutionary rates and coalescent effective population size.

91 ta and allow comparisons between models, the coalescent effective size should be recast as a kind of

92 of algorithms that offers fast and accurate "coalescent embedding" in the hyperbolic circle even for

93 Because multiple merger coalescents emerge in many models of rapid adaptation, w

94 10(-3) substitutions per site per year, and coalescent estimates place its emergence between 1991 an

95 Using coalescent estimation of the scaled population size para

96 draw particular attention to multiple-merger coalescent events and background selection, discuss pote

97 sed into components of waiting times between coalescent events and of tree topology.

98 ithin this continuum based on extinction and coalescent events.

99 s the DTWF model for the recent past and the coalescent for the more distant past.

100 ral model of recurrent selective sweeps in a coalescent framework, one that generalizes the recurrent

101 tationally challenging to study jointly in a coalescent framework.

102 ixed populations, and importance sampling of coalescent genealogies.

103 A coalescent genealogy for the reference haplotype data is

104 e posterior probability distribution, then a coalescent genealogy is simulated which extends the samp

105 dded based on the structure of the simulated coalescent genealogy.

106 on of compact coalescent histories: multiple coalescent histories are represented by a single compact

107 lter, where they enumerate all the so-called coalescent histories for the given species tree and the

108 algorithm is based on the notion of compact coalescent histories: multiple coalescent histories are

109 asian admixture can bias inferences on their coalescent history and confound genetic signals from ada

110 taneously describes the duplication-loss and coalescent history of a gene family.

111 istories are represented by a single compact coalescent history.

112 The sequentially Markov coalescent is a simplified genealogical process that aim

113 carrying capacity and subsequently follow a coalescent-like diversification process.

114 e inference method (called STELLSH) based on coalescent likelihood.

115 quantity of key interest when approximating coalescent likelihoods.

116 on, flat-center polygon, low center polygon, coalescent low center polygon, polygon trough, meadow, p

117 cosi2 implements coalescent machinery efficiently by tracking only a smal

118 s modeled via the modified sequential Markov coalescent (Marjoram and Wall, Genetics 7:16, 2006).

119 cally, recent advances in the application of coalescent, maximum likelihood (ML), and Bayesian method

120 Here, we present a coalescent method to jointly simulate MLST data and the

121 Using Bayesian coalescent methods applied to time-stamped sequences, we

122 The approximate or summary coalescent methods are computationally fast and are appl

123 We show that it is superior to established coalescent methods for reconstructing the topology and n

124 The coalescent methods for species tree reconstruction are i

125 ence strains using phylogenetic and Bayesian coalescent methods.

126 er estimates, as suggested from past work on coalescent methods.

127 istically consistent under the multi-species coalescent model and which is more accurate than other c

128 o, using the pairwise sequentially Markovian coalescent model applied to the complete diploid genome

129 When the sample size is large, the coalescent model becomes an increasingly inaccurate appr

130 served sequence data likelihood exploiting a coalescent model for the sampled individuals' genealogy

131 A coalescent model is developed for a large class of popul

132 many cases the (conceptually wrong) standard coalescent model is difficult to reject statistically an

133 Simulation under the coalescent model is ubiquitous in the analysis of geneti

134 ions can be captured by a spatially explicit coalescent model recently proposed by Etheridge (2008) a

135 nsive imputation experiments, we introduce a coalescent model that considers imputation accuracy in t

136 Phylodynamic inference uses a coalescent model that defines a probability density for

137 bable transmission pairs, were used to fit a coalescent model to determine the number of single nucle

138 cies), we applied the Generalized Mixed Yule-Coalescent model to explore potential cryptic diversity

139 distributions of FST and dx under a neutral coalescent model to identify putative targets of selecti

140 Here, we use an HIV-1 within-host coalescent model to probabilistically evaluate transmiss

141 In fact, the limiting coalescent model under a high rate of sweeps to low freq

142 The multispecies coalescent model underlies many approaches used for spec

143 lationships among quartets of taxa under the coalescent model using techniques from algebraic statist

144 from synthetic data sets simulated under the coalescent model with recombination, isolation, and migr

145 o capture the essential features of the full coalescent model with recombination, while being scalabl

146 od using a variety of data simulated under a coalescent model, before applying it to data from the 10

147 e assume that such a genealogy is known, the coalescent model, equipped with a Gaussian process prior

148 atistical guarantees under the multi-species coalescent model, existing methods are too computational

149 is monophyletic under a two-species neutral coalescent model, has been used in many studies.

150 Under the multispecies coalescent model, lineages may coalesce outside the spec

151 Using the multispecies coalescent model, we report a general analytical upper b

152 probabilities arising from the multispecies coalescent model, with an eye toward identifying feature

153 ineage sorting, modeled by the multi-species coalescent model.

154 s-level phylogenetic relationships under the coalescent model.

155 stically inconsistent under the multispecies coalescent model.

156 trees given a sample of gene trees under the coalescent model.

157 ic gene tree topology under the multispecies coalescent model.

158 ecies tree methods based on the multispecies coalescent model.

159 tral recombination graphs under a multilocus coalescent model.

160 phylogenetic methods using the multispecies coalescent model.

161 e polymorphism data and genetic maps using a coalescent modeling framework, we estimate the degree to

162 Coalescent modeling indicates that the timing of selecti

163 ysis of admixture, population structure, and coalescent modeling to demonstrate that the golden-crown

164 e generally, we show that spatially explicit coalescent models can be successfully integrated into mo

165 We develop coalescent models for autotetraploid species with tetras

166 Here we develop coalescent models for neutral sites on these chromosomes

167 ng epidemiological models to genealogies via coalescent models remains a challenging task, because pa

168 Logistic growth coalescent models reveal epidemic doubling times of 0.86

169 Using recently developed structured coalescent models that accommodate complex population dy

170 These approaches rely on coalescent models that may not be appropriate for infect

171 We use simulated sequence data based on coalescent models to show that our permutation strategy

172 There has been increasing interest in coalescent models which admit multiple mergers of ancest

173 under a number of different phylogenetic and coalescent models.

174 The multispecies coalescent (MSC) model has emerged as a powerful framewo

175 The multiple sequentially Markovian coalescent (MSMC) analyzes the observed pattern of mutat

176 omes and the multiple sequentially Markovian coalescent (MSMC) approach, we estimated the genetic spl

177 some time point or mutational origin in the coalescent of a set of extant genes in a population.

178 roaches are promising for LD mapping, as the coalescent offers a good approximation to the evolutiona

179 Although the two models converge to the same coalescent or diffusion limit, in which the population s

180 Here, detailed Bayesian coalescent phylogenetic analyses are performed on 97 who

181 genealogical quantities of interest with the coalescent predictions.

182 We test six coalescent priors and six random sequence samples of H3N

183 To this end, a structured coalescent procedure is used to construct a model of bac

184 present a detailed algorithm to simulate the coalescent process in this model, and provide an efficie

185 amework based on Hamiltonian Monte Carlo for coalescent process models.

186 idual-based disease transmission model and a coalescent process taking place within each host.

187 o be generated by a common process (e.g. the coalescent process), it is well known that numerous othe

188 ge sorting, which is commonly modeled by the coalescent process.

189 inly motivated by, principles underlying the coalescent process.

190 ng maximum-likelihood estimator for the same coalescent process.

191 ampled from a single species history after a coalescent process.

192 Second, the coalescent processes at unlinked loci are correlated wit

193 r that correspond to distinct regimes in the coalescent processes of Eldon and Wakeley.

194 dity variance polymorphism are studied using coalescent processes structured by genetic backgrounds.

195 Hybrid-Lambda allows different coalescent processes to be specified for different popul

196 ealogies under multiple merger and Kingman's coalescent processes within species networks or species

197 ication-loss, gene transfer and multispecies coalescent processes.

198 certain marine invertebrates under different coalescent processes.

199 he same diffusion approximation but distinct coalescent processes; i.e., in this class of models, anc

200 and Durbin's pairwise sequentially Markovian coalescent (PSMC) both for the pig data and using simula

201 nd applied a pairwise sequentially Markovian coalescent (PSMC) model to 703 combinations of genomic h

202 , called the pairwise sequentially Markovian coalescent (PSMC), for a pair of chromosomes (or one dip

203 The first is that the coalescent rates within backgrounds are not jointly prop

204 rs based on a Markovian approximation to the coalescent scale well, but do not support simulation of

205 A coalescent simulation algorithm was used to study this m

206 Coalescent simulation has become an indispensable tool i

207 The software performs coalescent simulation in the framework of approximate Ba

208 Coalescent simulation is pivotal for understanding popul

209 This allows exact coalescent simulation of new haplotype data, compared wi

210 Based on a coalescent simulation of the nucleotide variation of the

211 accurately we introduce FTEC, an easy-to-use coalescent simulation program capable of simulating hapl

212 Therefore, existing coalescent simulation programs can be adapted to study p

213 , or generated via integration with external coalescent simulation programs such as MaCS.

214 t by performing a standard backwards-in-time coalescent simulation while restricting coalescence to n

215 tor that supports both exact and approximate coalescent simulation with positive selection.

216 ose that establishing significance levels by coalescent simulation with recombination can improve the

217 Through coalescent simulation, REJECTOR generates numerous gene

218 superior to currently available methods for coalescent simulation.

219 , another attribute lacking in ABC and other coalescent-simulation approaches.

220 proach that combines ancient DNA techniques, coalescent simulations and species distribution modellin

221 Coalescent simulations are conducted to show that our ap

222 Coalescent simulations are used to generate the expected

223 results of species distribution models with coalescent simulations based on DNA sequences to explore

224 Present day coalescent simulations do not scale well, or use approxi

225 c scenarios are tested using Bayesian serial coalescent simulations in an approximate Bayesian comput

226 Multilocus coalescent simulations indicate that moths on different

227 SSRs and putatively neutral sequenced loci, coalescent simulations indicated that populations diverg

228 e ms remains an excellent choice for general coalescent simulations of DNA sequences, MaCS and fastsi

229 lades of a binary gene tree, and then employ coalescent simulations to assess the likelihood of the o

230 y of selection tests in concert with neutral coalescent simulations to demonstrate a signal of adapti

231 Here, we use coalescent simulations to measure the power of sets of S

232 By comparison with results from coalescent simulations, the observed allelic frequency s

233 dictions of population genetics theory using coalescent simulations, we estimate that a typical gene

234 Using coalescent simulations, we show how polymorphism, site f

235 ion and to implement efficient backward-time coalescent simulations, which can be used to predict how

236 ubstantial genotyping error, as validated in coalescent simulations.

237 Here we describe discoal, a coalescent simulator able to generate population samples

238 rate a statistical pipeline that couples the coalescent simulator of Kelleher et al. (2014) that simu

239 into two demes and then construct a flexible coalescent simulator that can generate samples under com

240 , implemented as the program MaCS (Markovian Coalescent Simulator), that can efficiently simulate hap

241 Although ms represents a popular standard coalescent simulator, it lacks the ability to simulate s

242 ly compared performances of five widely used coalescent simulators - Hudson's ms, msHOT, MaCS, Simcoa

243 A plethora of coalescent simulators are developed, but selecting the m

244 conversion is not supported by any published coalescent simulators that support selection.

245 Because, unlike coalescent simulators, it works forwards through time, i

246 od is a powerful alternative to the existing coalescent skyline plot, providing insight into the diff

247 d on a similar idea to the sequential Markov coalescent (SMC)-an approximation of the coalescent with

248 With coalescent spatially explicit simulations, we examined t

249 anomaly zone" where a failure to account for coalescent stochasticity will mislead phylogenetic infer

250 Demographic modeling and coalescent tests suggest that J. microsperma experienced

251 h as the Wright-Fisher model and the Kingman coalescent that do not adequately describe bacterial pop

252 ffective coalescent theory (a "fitness-class coalescent") that describes how positive selection at ma

253 Here, we introduce an effective coalescent theory (a "fitness-class coalescent") that de

254 s such as Kimura's neutral theory, Kingman's coalescent theory and efficient software such as BLAST,

255 -time approach to population genetics called coalescent theory as it is applied to diploid biparental

256 Coalescent theory attempts to link the phylogenetic hist

257 Coalescent theory deals with the dynamics of how sampled

258 ay random models of reproduction are used in coalescent theory is not justified.

259 Coalescent theory is routinely used to estimate past pop

260 While early work in coalescent theory only considered simple demographic mod

261 Coalescent theory plays an increasingly important role i

262 Coalescent theory provides an efficient framework for su

263 , we employ a theoretical framework based on coalescent theory to test for statistical significance o

264 as the framework connecting evolutionary and coalescent theory with the analysis of genetic data obse

265 ter simulation of vicariance on the basis of coalescent theory, EIGENSOFT systematically overestimate

266 Specifically, using coalescent theory, we calculate the variance of the tota

267 odel, within a likelihood framework based on coalescent theory, we can jointly study demographic hist

268 structed the epidemic history of 2k/1b using coalescent theory-based methods, matching patterns previ

269 tiple mergers are unlikely under the neutral coalescent, they create a unique genetic footprint in ad

270 bonobo sequences, and assuming a chimp-human coalescent time of 5 million years before present, we fi

271 first derive analytic equations for pairwise coalescent times and FST as a function of time after the

272 ting for 64% of our sample, have very recent coalescent times, ranging between 3.5 and 7.3 KYA.

273 smission inference called SCOTTI (Structured COalescent Transmission Tree Inference).

274 a new reconciliation structure, the labeled coalescent tree (LCT), that simultaneously describes coa

275 ough a reconciliation structure, the labeled coalescent tree (LCT), that simultaneously describes the

276 CT to a new structure, the partially labeled coalescent tree (PLCT) and demonstrate how to use the PL

277 ling and labeled taxa, and how to simulate a coalescent tree conditional on a complex demographic his

278 olymorphisms is presented, using the general coalescent tree framework and the infinite-sites model f

279 The general coalescent tree framework is a family of models for dete

280 ribution of branch lengths in the underlying coalescent tree.

281 Here, we infer multilocus coalescent trees from >1000 nuclear single-nucleotide po

282 s longer segments of genome, the sequence of coalescent trees is modeled via the modified sequential

283 A population tree with branch lengths in coalescent units is estimated from quartet concordance f

284 time to be converted between generations and coalescent units, by specifying a population size for ea

285 nse, it may be difficult to reject Kingman's coalescent using genetic data.

286 es over a region of 1 Mb simulated under the coalescent were used to estimate LD using the two measur

287 hem; here, the genealogical framework of the coalescent will continue to be conceptually and analytic

288 kov coalescent (SMC)-an approximation of the coalescent with crossover recombination.

289 ne conversion in eukaryotes, i.e., using the coalescent with gene conversion (CGC).

290 a simplification of the previously described coalescent with gene conversion.

291 We present a new model that approximates the coalescent with gene conversion: the bacterial sequentia

292 Using these tools, exact simulation of the coalescent with recombination for chromosome-sized regio

293 Simulation of genomic sequences under the coalescent with recombination has conventionally been im

294 Unfortunately, the true CSD under the coalescent with recombination is not known, so approxima

295 We present the sequential coalescent with recombination model (SCRM), a new method

296 nt demographic inference method based on the coalescent with recombination, and is able to incorporat

297 efficiently and accurately approximates the coalescent with recombination, closing the gap between c

298 arkovian coalescent, an approximation to the coalescent with recombination, to include the effects of

299 om the diffusion process associated with the coalescent with recombination.

300 may be approximated using Kingman's standard coalescent, with a coalescent effective population size