ライフサイエンスコーパス: coalescent

1 well as its accuracy under the multispecies coalescent.

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

3 gene tree topologies under the multispecies coalescent.

4 izing the whole assignment process under the coalescent.

5 data from an island model using the neutral coalescent.

6 acilitates testing for deviations from the n-coalescent.

7 ved model fit of the f-coalescent over the n-coalescent.

8 ference on these data under the multispecies coalescent.

9 led genetic structure under the multispecies coalescent.

10 or exploiting the inherent symmetries of the coalescent.

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

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

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

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

15 Coalescent analyses indicate that P. filamentosus may ha

16 Bayesian coalescent analyses indicated that this variant arose in

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

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

19 In both genera, coalescent analyses recovered almost all nominal taxa as

20 understand genomic plasticity and to perform coalescent analyses.

21 23, which had an origin in 1908 as dated by coalescent analysis and included isolates with a diverge

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

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

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

25 ) and maximum likelihood (ML) searches and a coalescent analysis of species trees.

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

27 Coalescent analysis revealed that although the genetic d

28 Coalescent analysis shows that the Khoisan and their anc

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

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

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

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

33 ed through comparative genomics and Bayesian coalescent analysis.

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

35 We used coalescent and assignment methods to investigate the tim

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

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

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

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

40 ological evidence, were recovered across the coalescent and integrated nuclear phylogeny.

41 The development of the f-coalescent and its inclusion into the inference program

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

43 that allows us to explicitly model the joint coalescent and reassortment process.

44 lgorithm provides the means to jointly infer coalescent and reassortment rates with the reassortment

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

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

47 When [Formula: see text], the f-coalescent and the Kingman's n-coalescent are equivalent

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

49 By integrating Bayesian coalescent and trait analyses, this study demonstrates a

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

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

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

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

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

55 We use variant antigen profiling, coalescent approaches and experimental infections to sho

56 nes in a time interval of length T for the f-coalescent are derived.

57 text], the f-coalescent and the Kingman's n-coalescent are equivalent.

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

59 tabulations seemed to develop in regions of coalescent areas of RORA.

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

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

62 The coalescent-based analysis revealed strong evidence for d

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

64 Notably, coalescent-based ASTRAL species phylogenies inferred fro

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

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

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

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

69 Coalescent-based inference required fewer sampled indivi

70 mbines a fast heuristic search with accurate coalescent-based likelihood calculations.

71 GTmix performs coalescent-based maximum likelihood inference of admixtu

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

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

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

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

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

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

78 Using a combination of assignment and coalescent-based methods, we show that the Cape hare is

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

80 Here, we introduce a coalescent-based model that allows us to explicitly mode

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

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

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

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

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

86 Coalescent-based simulation software for genomic sequenc

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

88 Although coalescent-based species tree estimation methods can hav

89 ficient simulation of genetic data under the coalescent becomes a primary challenge.

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

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

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

93 rated with known alpha values and that the f-coalescent can detect potential environmental heterogene

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

95 i and Stephens model, which approximates the coalescent describing the pattern of variation in a popu

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

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

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

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

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

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

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

103 Using coalescent estimation of the scaled population size para

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

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

106 ithin this continuum based on extinction and coalescent events.

107 n approach to the coalescent, the fractional coalescent (f-coalescent), is introduced.

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

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

110 tationally challenging to study jointly in a coalescent framework.

111 ixed populations, and importance sampling of coalescent genealogies.

112 A coalescent genealogy for the reference haplotype data is

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

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

115 discovery (ABGD), and generalized mixed Yule-coalescent (GMYC).

116 The f-coalescent has been implemented in the population geneti

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

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

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

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

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

122 istories are represented by a single compact coalescent history.

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

124 the coalescent, the fractional coalescent (f-coalescent), is introduced.

125 Here we derive F(ST) values from multi-locus coalescent isolation-with-migration models, and couple t

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

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

128 quantity of key interest when approximating coalescent likelihoods.

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

130 cosi2 implements coalescent machinery efficiently by tracking only a smal

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

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

133 e reusable, we implement several variants of coalescent mergers, including an approximation where low

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

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

136 The coalescent methods for species tree reconstruction are i

137 sis, for methods validation and for teaching coalescent methods in an interactive and visual environm

138 data to the question by using supertree and coalescent methods to interrogate >3,000 gene families i

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

154 The multispecies coalescent model underlies many approaches used for spec

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

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

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

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

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

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

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

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

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

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

165 ecies tree methods based on the multispecies coalescent model.

166 tral recombination graphs under a multilocus coalescent model.

167 phylogenetic methods using the multispecies coalescent model.

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

169 s-level phylogenetic relationships under the coalescent model.

170 stically inconsistent under the multispecies coalescent model.

171 ic gene tree topology under the multispecies coalescent model.

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

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

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

175 We develop coalescent models for autotetraploid species with tetras

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

177 Logistic growth coalescent models reveal epidemic doubling times of 0.86

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

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

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

181 under a number of different phylogenetic and coalescent models.

182 ation rate and generation time, multispecies coalescent (MSC) methods can potentially overcome these

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

184 alogies based on the well-known multispecies coalescent (MSC) model.

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

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

187 genome-wide data we estimated the long-term coalescent N(e) for 17 pinniped species represented by 3

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

189 sites) showed an improved model fit of the f-coalescent over the n-coalescent.

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

191 genealogical quantities of interest with the coalescent predictions.

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

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

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

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

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

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

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

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

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

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

202 certain marine invertebrates under different coalescent processes.

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

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

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

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

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

208 Coalescent simulation has become an indispensable tool i

209 Coalescent simulation is pivotal for understanding popul

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

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

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

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

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

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

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

217 superior to currently available methods for coalescent simulation.

218 Finally, we employed spatially-explicit coalescent simulations and an approximate Bayesian compu

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

220 Coalescent simulations are conducted to show that our ap

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

222 Coalescent simulations confirm that there is elevated nu

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

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

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

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

227 Approximate Bayesian computations based on coalescent simulations showed that the post-glacial asse

228 Coalescent simulations suggest that all of these populat

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

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

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

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

233 ubstantial genotyping error, as validated in coalescent simulations.

234 ongly affects the relevant algorithm for the coalescent simulator (e.g. only when n<2m, it is reasona

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

236 tion sizes, migration events) to the msprime coalescent simulator by parsing a user-supplied species

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

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

239 population genetic models using the msprime coalescent simulator that have found their way into the

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

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

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

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

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

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

246 With coalescent spatially explicit simulations, we examined t

247 Although highly efficient compared to the coalescent, standard implementations of this model still

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

249 hood, Bayesian inference, and a multispecies coalescent summary method, and evaluated support for alt

250 BTB inversion barrier (~12 kcal/mol) at the coalescent temperature (248 K), which was estimated by v

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

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

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

254 er model (or similar models) and the Kingman coalescent, the cornerstones of mathematical population

255 An approach to the coalescent, the fractional coalescent (f-coalescent), is

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

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

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 ion event can occur, reducing their expected coalescent time below that given by the simple approxima

271 weep is negligible compared with the neutral coalescent time.

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

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

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

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

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

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

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

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

280 Moreover, the well-supported coalescent tree inferred here differs from previous stud

281 ribution of branch lengths in the underlying coalescent tree.

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

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

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

285 the ML tree with estimated branch lengths in coalescent units.

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

287 Moreover, many simulators are based on the coalescent, which assumes a neutral model of genomic evo

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

289 reproduction and associated multiple-merger coalescents will become at least as relevant as the Wrig

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

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

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

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

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

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