scholarly journals Estimating seven coefficients of pairwise relatedness using population genomic data

2016 ◽  
Author(s):  
Matthew S Ackerman ◽  
Parul Johri ◽  
Ken Spitze ◽  
Sen Xu ◽  
Thomas Doak ◽  
...  
Keyword(s):  
Numerical Optimization ◽  
Daphnia Pulex ◽  
Correlation Coefficients ◽  
Genomic Data ◽  
Optimization Procedure ◽  
Genotypic Correlation ◽  
New Methods ◽  
Population Genomic ◽  
Identical By Descent ◽  
Freshwater Crustacean

ABSTRACTPopulation structure can be described by genotypic correlation coefficients between groups of individuals, the most basic of which are the pair-wise relatedness coefficients between any two individuals. There are nine pair-wise relatedness coefficients in the most general model, and we show that these can be reduced to seven coefficients for biallelic loci. Although all nine coefficients can be estimated from pedigrees, six coefficients have been beyond empirical reach. We provide a numerical optimization procedure that estimates them from population-genomic data. Simulations show that the procedure is nearly unbiased, even at 3× coverage, and errors in five of the seven coefficients are statistically uncorrelated. The remaining two coefficients have a negative correlation of errors, but their sum provides an unbiased assessment of the overall correlation of heterozygosity between two individuals. Application of these new methods to four populations of the freshwater crustacean Daphnia pulex reveal the occurrence of half-siblings in our samples, as well as a number of identical individuals that are likely obligately asexual clone-mates. Statistically significant negative estimates of these pair-wise relatedness coefficients, including inbreeding coefficents that were typically negative, underscore the difficulties that arise when interpreting genotypic correlations as estimations of the probability that alleles are identical by descent.

scholarly journals Population genomic data in spider mites point to a role for local adaptation in shaping range shifts

2020 ◽  
Vol 13 (10) ◽  
pp. 2821-2835
Author(s):  
Lei Chen ◽  
Jing‐Tao Sun ◽  
Peng‐Yu Jin ◽  
Ary A. Hoffmann ◽  
Xiao‐Li Bing ◽  
...  
Keyword(s):  
Local Adaptation ◽  
Genomic Data ◽  
Spider Mites ◽  
Range Shifts ◽  
Population Genomic

scholarly journals Combined Magnetohydrodynamic and Geometric Optimization of a Hypersonic Inlet

2009 ◽  
Vol 2009 ◽  
pp. 1-12 ◽  
Author(s):  
Kamesh Subbarao ◽  
Jennifer D. Goss
Keyword(s):  
Magnetic Field ◽  
Numerical Optimization ◽  
Splitting Method ◽  
Optimization Procedure ◽  
Geometric Optimization ◽  
Control Parameters ◽  
Flow Solution ◽  
Hypersonic Inlet ◽  
Mass Capture ◽  
The Magnetic Field

This paper considers the numerical optimization of a double ramp scramjet inlet using magnetohydrodynamic (MHD) effects together with inlet ramp angle changes. The parameter being optimized is the mass capture at the throat of the inlet, such that spillage effects for less than design Mach numbers are reduced. The control parameters for the optimization include the MHD effects in conjunction with ramp angle changes. To enhance the MHD effects different ionization scenarios depending upon the alignment of the magnetic field are considered. The flow solution is based on the Advection Upstream Splitting Method (AUSM) that accounts for the MHD source terms as well. A numerical Broyden-Flecher-Goldfarb-Shanno- (BFGS-) based procedure is utilized to optimize the inlet mass capture. Numerical validation results compared to published results in the literature as well as the outcome of the optimization procedure are summarized to illustrate the efficacy of the approach.

scholarly journals Inferring Adaptive Introgression Using Hidden Markov Models

2020 ◽  
Author(s):  
Jesper Svedberg ◽  
Vladimir Shchur ◽  
Solomon Reinman ◽  
Rasmus Nielsen ◽  
Russell Corbett-Detig
Keyword(s):  
Markov Models ◽  
Hidden Markov ◽  
Genomic Data ◽  
Diverse Populations ◽  
Powerful Method ◽  
Adaptive Genetic Variation ◽  
Adaptive Introgression ◽  
Population Genomic ◽  
Significant Interest ◽  
Selection Parameters

AbstractAdaptive introgression - the flow of adaptive genetic variation between species or populations - has attracted significant interest in recent years and it has been implicated in a number of cases of adaptation, from pesticide resistance and immunity, to local adaptation. Despite this, methods for identification of adaptive introgression from population genomic data are lacking. Here, we present Ancestry_HMM-S, a Hidden Markov Model based method for identifying genes undergoing adaptive introgression and quantifying the strength of selection acting on them. Through extensive validation, we show that this method performs well on moderately sized datasets for realistic population and selection parameters. We apply Ancestry_HMM-S to a dataset of an admixed Drosophila melanogaster population from South Africa and we identify 17 loci which show signatures of adaptive introgression, four of which have previously been shown to confer resistance to insecticides. Ancestry_HMM-S provides a powerful method for inferring adaptive introgression in datasets that are typically collected when studying admixed populations. This method will enable powerful insights into the genetic consequences of admixture across diverse populations. Ancestry_HMM-S can be downloaded from https://github.com/jesvedberg/Ancestry_HMM-S/.

scholarly journals Combining Analytical Models and Mesh Morphing Based Optimization Techniques for the Design of Flying Multihulls Appendages

2021 ◽  
Vol 6 (01) ◽  
pp. 151-172
Author(s):  
Ubaldo Cella ◽  
Corrado Groth ◽  
Stefano Porziani ◽  
Alberto Clarich ◽  
Francesco Franchini ◽  
...  
Keyword(s):  
Numerical Optimization ◽  
Fluid Dynamic ◽  
Optimization Procedure ◽  
Optimization Techniques ◽  
Analytical Models ◽  
High Fidelity ◽  
Mesh Morphing ◽  
Wide Range ◽  
Global Equilibrium ◽  
Range Of Values

Abstract The fluid dynamic design of hydrofoils involves most of the typical difficulties of aeronautical wings design with additional complexities related to the design of a device operating in a multiphase environment. For this reason, “high fidelity” analysis solvers should be, in general, adopted also in the preliminary design phase. In the case of modern fast foiling sailing yachts, the appendages accomplish both the task of lifting up the boat and to make possible upwind sailing by contributing balance to the sail side force and the heeling moment. Furthermore, their operative design conditions derive from the global equilibrium of forces and moments acting on the system which might vary in a very wide range of values. The result is a design problem defined by a large number of variables operating in a wide design space. In this scenario, the device performing in all conditions has to be identified as a trade-off among several conflicting requirements. One of the most efficient approaches to such a design challenge is to combine multi-objective optimization strategies with experienced aerodynamic design. This paper presents a numerical optimization procedure suitable for foiling multihulls. As a proof of concept, it reports, as an application, the foils design of an A-Class catamaran. The key point of the method is the combination of opportunely developed analytical models of the hull forces with high fidelity multiphase analyses in both upwind and downwind sailing conditions. The analytical formulations were tuned against a database of multiphase analyses of a reference demihull at several attitudes and displacements. An aspect that significantly contributes to both efficiency and robustness of the method is the approach adopted to the geometric parametrization of the foils which was implemented by a mesh morphing technique based on Radial Basis Functions.

scholarly journals Estimating Seven Coefficients of Pairwise Relatedness Using Population-Genomic Data

Genetics ◽  
2017 ◽  
Vol 206 (1) ◽  
pp. 105-118 ◽  
Author(s):  
Matthew S. Ackerman ◽  
Parul Johri ◽  
Ken Spitze ◽  
Sen Xu ◽  
Thomas G. Doak ◽  
...  
Keyword(s):  
Genomic Data ◽  
Population Genomic

scholarly journals Equitable Expanded Carrier Screening Needs Indigenous Clinical and Population Genomic Data

2020 ◽  
Vol 107 (2) ◽  
pp. 175-182
Author(s):  
Simon Easteal ◽  
Ruth M. Arkell ◽  
Renzo F. Balboa ◽  
Shayne A. Bellingham ◽  
Alex D. Brown ◽  
...  
Keyword(s):  
Genomic Data ◽  
Carrier Screening ◽  
Expanded Carrier Screening ◽  
Population Genomic

scholarly journals Discovery of meaningful associations in genomic data using partial correlation coefficients

2004 ◽  
Vol 20 (18) ◽  
pp. 3565-3574 ◽  
Author(s):  
A. de la Fuente ◽  
N. Bing ◽  
I. Hoeschele ◽  
P. Mendes
Keyword(s):  
Partial Correlation ◽  
Correlation Coefficients ◽  
Genomic Data

Optimization for Slip Analysis of Belt Drives With Finite Element Verification

2013 ◽  
Author(s):  
Muhammad M. Hussein ◽  
Bassam A. Hussein ◽  
Sayed M. Metwalli
Keyword(s):  
Finite Element ◽  
Numerical Optimization ◽  
Optimization Procedure ◽  
Belt Drives ◽  
Normal Forces ◽  
Highly Nonlinear ◽  
Three Stages ◽  
System Variables ◽  
Realistic Prediction ◽  
Belt System

This paper presents optimized nonlinear analytical procedure for the slipping and sticking motion of extensible belt pulley systems. The procedure initially assumes a general spline representing the changes in the internal moment along the slipping zones. This assumption enables one to get the shear force values along the belt length. Also this assumption enabled us to discover an entrance slipping zone of the belt pulley contact with all variables changing along this zone. The contact between the belt and the pulley has thus three stages that lead to more realistic prediction of the belt system variables and more accurate values for the angles in the belt pulley sliding zones. The change in the angular velocity of the driven pulley with respect to the driving pulley, the change in the cross section dimensions, and the belt stretch are predicted. The analytical model gives highly nonlinear equations which are solved by numerical optimization procedure and validated by the solution obtained using absolute nodal coordinate formulation (ANCF) finite element method. The results obtained demonstrate that the present formulation leads to more accurate prediction for the belt tension, friction and normal forces. This paper presents the analytical results of several models which are presented and would enable better prediction for the critical loads for several cases.

FIFS: A data mining method for informative marker selection in high dimensional population genomic data

2017 ◽  
Vol 90 ◽  
pp. 146-154 ◽  
Author(s):  
Ioannis Kavakiotis ◽  
Patroklos Samaras ◽  
Alexandros Triantafyllidis ◽  
Ioannis Vlahavas
Keyword(s):  
Data Mining ◽  
Genomic Data ◽  
High Dimensional ◽  
Mining Method ◽  
Informative Marker ◽  
Data Mining Method ◽  
Marker Selection ◽  
Population Genomic
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