scholarly journals QUETZAL - an open source C++ template library for coalescence-based environmental demogenetic models inference

2017 ◽  
Author(s):  
Arnaud Becheler ◽  
Camille Coron ◽  
Stéphane Dupas
Keyword(s):  
Population Growth ◽  
Open Source ◽  
Approximate Bayesian Computation ◽  
Changing Environment ◽  
Implementation Framework ◽  
Computation Techniques ◽  
Wide Range ◽  
Template Library ◽  
And Migration ◽  
Approximate Bayesian

1AbstractThe purpose of this article is to introduce an implementation framework enabling us, using available genetic samples, to understand and foresee the behavior of species living in a fragmented and temporally changing environment. To this aim, we first present a model of coalescence which is conditioned to environment, through an explicit modeling of population growth and migration. The parameters of this model can be infered using Approximate Bayesian Computation techniques, which supposes that the considered model can be efficiently simulated. We next present Quetzal, a C++ library composed of reusable generic components and designed to efficiently implement a wide range of coalescence-based environmental demogenetic models.

scholarly journals Some patterns and social impacts of external migration on a below-replacement population: Denmark by the turn of the millennium

1996 ◽  
pp. 136-149
Author(s):  
Hans O Hansen ◽  
Paul S. Maxim
Keyword(s):  
Population Growth ◽  
Social Impacts ◽  
Turn Of The Millennium ◽  
Differential Fertility ◽  
The Past ◽  
Naturalized Citizens ◽  
Wide Range ◽  
And Migration ◽  
The Impact ◽  
External Migration

As with many other nations in Europe, Denmark has experienced below-replacement fertility over the past three decades. The impact on population growth of the recent fertility decline to a large extent has been offset by a positive net balance of external migration. To provide a factual basis for a wide range of policy issues and social and cultural impacts we start by studying external migration, differential fertility, naturalization of foreign nationals, and population growth in the framework of multidimensional life models. Migrants and naturalized citizens tend to have reproductive behavior and sex/age profiles that differ significantly from those of the remaining population. To study some concerted demographic and social impacts of such differentials, we construct a number of midterm projections based on existing and expected development of fertility, mortality, and migration.

scholarly journals Substructured population growth in the Ashkenazi Jews inferred with Approximate Bayesian Computation

2018 ◽  
Author(s):  
Ariella L. Gladstein ◽  
Michael F. Hammer
Keyword(s):  
Population Growth ◽  
Central Europe ◽  
Population Differentiation ◽  
Approximate Bayesian Computation ◽  
Middle Eastern ◽  
Snp Array ◽  
Bayesian Computation ◽  
Ashkenazi Jews ◽  
Effective Population ◽  
Approximate Bayesian

The Ashkenazi Jews (AJ) are a population isolate that have resided in Central Europe since at least the 10th century and share ancestry with both European and Middle Eastern populations. Between the 11th and 16th centuries, AJ expanded eastward leading to two culturally distinct communities, one in central Europe and one in eastern Europe. Our aim was to determine if there are genetically distinct AJ subpopulations that reflect the cultural groups, and if so, what demographic events contributed to the population differentiation. We used Approximate Bayesian Computation (ABC) to choose among models of AJ history and infer demographic parameter values, including divergence times, effective population size, and gene flow. For the ABC analysis we used allele frequency spectrum and identical by descent based statistics to capture information on a wide timescale. We also mitigated the effects of ascertainment bias when performing ABC on SNP array data by jointly modeling and inferring the SNP discovery. We found that the most likely model was population differentiation between the Eastern and Western AJ ~400 years ago. The differentiation between the Eastern and Western AJ could be attributed to more extreme population growth in the Eastern AJ (0.25 per generation) than the Western AJ (0.069 per generation).

scholarly journals Quantifying cell line specific proliferation and migration rates in glioblastoma cells

2019 ◽  
Author(s):  
Emil Rosén ◽  
Philip Gerlee ◽  
Sven Nelander
Keyword(s):  
Cell Lines ◽  
Approximate Bayesian Computation ◽  
Patient Specific ◽  
Glioblastoma Cell ◽  
Migration Rates ◽  
Computation Algorithm ◽  
And Migration ◽  
Approximate Bayesian ◽  
Glioblastoma Cell Lines ◽  
Proliferation And Migration

AbstractWe have characterised the migration and proliferation rates of a large number of patient-derived glioblastoma cell lines using an individual-based model coupled to an Approximate Bayesian Computation algorithm. We found that the cell lines exhibited a negative correlation between the rate of migration and rate of division. This observation agrees with the Go or Grow hypothesis and highlights patient-specific differences in migration and proliferation.

scholarly journals Inferring population size history from large samples of genome wide molecular data - an approximate Bayesian computation approach

2016 ◽  
Author(s):  
Simon Boitard ◽  
Willy Rodriguez ◽  
Flora Jay ◽  
Stefano Mona ◽  
Frederic Austeritz
Keyword(s):  
Population Genetics ◽  
Population Size ◽  
Effective Population Size ◽  
Approximate Bayesian Computation ◽  
Recent Common Ancestor ◽  
Bayesian Computation ◽  
Effective Population ◽  
Wide Range ◽  
Complete Genomes ◽  
Approximate Bayesian

Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey), PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles.

scholarly journals Substructured Population Growth in the Ashkenazi Jews Inferred with Approximate Bayesian Computation

2019 ◽  
Vol 36 (6) ◽  
pp. 1162-1171 ◽  
Author(s):  
Ariella L Gladstein ◽  
Michael F Hammer
Keyword(s):  
Population Growth ◽  
Population Differentiation ◽  
Approximate Bayesian Computation ◽  
Middle Eastern ◽  
Snp Array ◽  
Bayesian Computation ◽  
Ashkenazi Jews ◽  
Effective Population ◽  
Abc Analysis ◽  
Approximate Bayesian

Abstract The Ashkenazi Jews (AJ) are a population isolate sharing ancestry with both European and Middle Eastern populations that has likely resided in Central Europe since at least the tenth century. Between the 11th and 16th centuries, the AJ population expanded eastward leading to two culturally distinct communities in Western/Central and Eastern Europe. Our aim was to determine whether the western and eastern groups are genetically distinct, and if so, what demographic processes contributed to population differentiation. We used Approximate Bayesian Computation to choose among models of AJ history and to infer demographic parameter values, including divergence times, effective population sizes, and levels of gene flow. For the ABC analysis, we used allele frequency spectrum and identical by descent-based statistics to capture information on a wide timescale. We also mitigated the effects of ascertainment bias when performing ABC on SNP array data by jointly modeling and inferring SNP discovery. We found that the most likely model was population differentiation between Eastern and Western AJ ∼400 years ago. The differentiation between the Eastern and Western AJ could be attributed to more extreme population growth in the Eastern AJ (0.250 per generation) than the Western AJ (0.069 per generation).

scholarly journals Weighted approximate Bayesian computation via Sanov’s theorem

2021 ◽  
Author(s):  
Cecilia Viscardi ◽  
Michele Boreale ◽  
Fabio Corradi
Keyword(s):  
Large Deviations ◽  
Posterior Distribution ◽  
Approximate Bayesian Computation ◽  
Bayesian Computation ◽  
Information Theoretic ◽  
Discrete Random Variables ◽  
Positive Weights ◽  
Approximate Bayesian ◽  
Information Theoretic Method ◽  
Computational Resources

AbstractWe consider the problem of sample degeneracy in Approximate Bayesian Computation. It arises when proposed values of the parameters, once given as input to the generative model, rarely lead to simulations resembling the observed data and are hence discarded. Such “poor” parameter proposals do not contribute at all to the representation of the parameter’s posterior distribution. This leads to a very large number of required simulations and/or a waste of computational resources, as well as to distortions in the computed posterior distribution. To mitigate this problem, we propose an algorithm, referred to as the Large Deviations Weighted Approximate Bayesian Computation algorithm, where, via Sanov’s Theorem, strictly positive weights are computed for all proposed parameters, thus avoiding the rejection step altogether. In order to derive a computable asymptotic approximation from Sanov’s result, we adopt the information theoretic “method of types” formulation of the method of Large Deviations, thus restricting our attention to models for i.i.d. discrete random variables. Finally, we experimentally evaluate our method through a proof-of-concept implementation.

Flow parameter estimation using laser absorption spectroscopy and approximate Bayesian computation

2021 ◽  
Vol 62 (2) ◽  
Author(s):  
Jason D. Christopher ◽  
Olga A. Doronina ◽  
Dan Petrykowski ◽  
Torrey R. S. Hayden ◽  
Caelan Lapointe ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Absorption Spectroscopy ◽  
Approximate Bayesian Computation ◽  
Flow Parameter ◽  
Bayesian Computation ◽  
Laser Absorption Spectroscopy ◽  
Laser Absorption ◽  
Approximate Bayesian
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