Literature DB >> 19176551

QMSim: a large-scale genome simulator for livestock.

Mehdi Sargolzaei1, Flavio S Schenkel.   

Abstract

SUMMARY: QMSim was designed to simulate large-scale genotyping data in multiple and complex livestock pedigrees. The simulation is basically carried out in two steps. In the first step, a historical population is simulated to establish mutation-drift equilibrium, and in the second step, recent population structures are generated, which can be very complex. A wide variety of genome architectures, ranging from infinitesimal model to single-locus model, can be simulated. The program is efficient in terms of computing time and memory requirements. AVAILABILITY: Executable versions of QMSim for Windows and Linux are freely available at http://www.aps.uoguelph.ca/~msargol/qmsim/.

Mesh:

Year:  2009        PMID: 19176551     DOI: 10.1093/bioinformatics/btp045

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  100 in total

1.  Accuracy of Genomic Prediction in Synthetic Populations Depending on the Number of Parents, Relatedness, and Ancestral Linkage Disequilibrium.

Authors:  Pascal Schopp; Dominik Müller; Frank Technow; Albrecht E Melchinger
Journal:  Genetics       Date:  2016-11-09       Impact factor: 4.562

2.  Quality control of genotypes using heritability estimates of gene content at the marker.

Authors:  Natalia S Forneris; Andres Legarra; Zulma G Vitezica; Shogo Tsuruta; Ignacio Aguilar; Ignacy Misztal; Rodolfo J C Cantet
Journal:  Genetics       Date:  2015-01-06       Impact factor: 4.562

3.  Genomic selection strategies for breeding adaptation and production in dairy cattle under climate change.

Authors:  Ismo Strandén; Juha Kantanen; Isa-Rita M Russo; Pablo Orozco-terWengel; Michael W Bruford
Journal:  Heredity (Edinb)       Date:  2019-03-18       Impact factor: 3.821

4.  Incorporating the single-step strategy into a random regression model to enhance genomic prediction of longitudinal traits.

Authors:  H Kang; L Zhou; R Mrode; Q Zhang; J-F Liu
Journal:  Heredity (Edinb)       Date:  2016-12-28       Impact factor: 3.821

5.  Orthogonal Estimates of Variances for Additive, Dominance, and Epistatic Effects in Populations.

Authors:  Zulma G Vitezica; Andrés Legarra; Miguel A Toro; Luis Varona
Journal:  Genetics       Date:  2017-05-18       Impact factor: 4.562

6.  Sparse single-step genomic BLUP in crossbreeding schemes.

Authors:  Jérémie Vandenplas; Mario P L Calus; Jan Ten Napel
Journal:  J Anim Sci       Date:  2018-06-04       Impact factor: 3.159

7.  Genomic prediction for crossbred performance using metafounders.

Authors:  Elizabeth M van Grevenhof; Jérémie Vandenplas; Mario P L Calus
Journal:  J Anim Sci       Date:  2019-02-01       Impact factor: 3.159

Review 8.  Genomic prediction in animals and plants: simulation of data, validation, reporting, and benchmarking.

Authors:  Hans D Daetwyler; Mario P L Calus; Ricardo Pong-Wong; Gustavo de Los Campos; John M Hickey
Journal:  Genetics       Date:  2012-12-05       Impact factor: 4.562

9.  Factors affecting GEBV accuracy with single-step Bayesian models.

Authors:  Lei Zhou; Raphael Mrode; Shengli Zhang; Qin Zhang; Bugao Li; Jian-Feng Liu
Journal:  Heredity (Edinb)       Date:  2017-11-23       Impact factor: 3.821

10.  Marker genotyping error effects on genomic predictions under different genetic architectures.

Authors:  Tahere Akbarpour; Navid Ghavi Hossein-Zadeh; Abdol Ahad Shadparvar
Journal:  Mol Genet Genomics       Date:  2020-09-29       Impact factor: 3.291

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