Geno-Diver is a combined coalescence and forward-in-time simulator designed to simulate complex traits with a quantitative and/or fitness component and implement multiple selection and mating strategies utilizing pedigree or genomic information. The simulation is carried out in two steps. The first step generates whole-genome sequence data for founder individuals. A variety of trait architectures can be gener- ated for quantitative and fitness traits along with their covariance. The second step generates new individuals forward-in-time based on a variety of selection and mat- ing scenarios. Genetic values are predicted for individuals utilizing pedigree or genomic information. Relationship matrices and their associated inverses are gener- ated using computationally efficient routines. We benchmarked Geno-Diver with a previous simulation program and described how to simulate a traditional quantita- tive trait along with a quantitative and fitness trait. A user manual with examples, source code in C++11 and executable versions of Geno-Diver for Linux are freely available at https://github.com/jeremyhoward/Geno-Diver.

Geno-Diver: A combined coalescence and forward-in-time simulator for populations undergoing selection for complex traits / Howard Jeremy; Tiezzi Francesco; Pryce Jenny; Maltecca Christian. - In: JOURNAL OF ANIMAL BREEDING AND GENETICS. - ISSN 0931-2668. - ELETTRONICO. - 134:(2017), pp. 553-563. [10.1111/jbg.12277]

Geno-Diver: A combined coalescence and forward-in-time simulator for populations undergoing selection for complex traits

Tiezzi Francesco;
2017

Abstract

Geno-Diver is a combined coalescence and forward-in-time simulator designed to simulate complex traits with a quantitative and/or fitness component and implement multiple selection and mating strategies utilizing pedigree or genomic information. The simulation is carried out in two steps. The first step generates whole-genome sequence data for founder individuals. A variety of trait architectures can be gener- ated for quantitative and fitness traits along with their covariance. The second step generates new individuals forward-in-time based on a variety of selection and mat- ing scenarios. Genetic values are predicted for individuals utilizing pedigree or genomic information. Relationship matrices and their associated inverses are gener- ated using computationally efficient routines. We benchmarked Geno-Diver with a previous simulation program and described how to simulate a traditional quantita- tive trait along with a quantitative and fitness trait. A user manual with examples, source code in C++11 and executable versions of Geno-Diver for Linux are freely available at https://github.com/jeremyhoward/Geno-Diver.
2017
134
553
563
Howard Jeremy; Tiezzi Francesco; Pryce Jenny; Maltecca Christian
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1258630
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