Portal de Periódicos da CAPES

Motivations and Constraints to Family Planning: A Qualitative Study in Rwanda’s Southern Kayonza District

2015; Johns Hopkins University Press; Volume: 3; Issue: 2 Linguagem: Inglês

10.9745/ghsp-d-14-00198

2169-575X

Didi Bertrand Farmer, Leslie Berman, Grace Ryan, Lameck Habumugisha, Paulin Basinga, Cameron T. Nutt, Francois Kamali, Elias Ngizwenayo, Jacklin St. Fleur, Peter Niyigena, Fidèle Ngabo, Paul E. Farmer, Michael Rich,

Adolescent Sexual and Reproductive Health

Abstract In the last decade the use of mixed models has become a pivotal part in the implementation of genome-assisted prediction in plant and animal breeding programs. Exploiting the use genetic correlation among traits through multivariate predictions has been proposed in recent years as a way to boost prediction accuracy and understand pleiotropy and other genetic and ecological phenomena better. Multiple mixed model solvers able to use relationship matrices or deal with marker-based incidence matrices have been released in the last years but multivariate versions are scarse. Such solvers have become quite popular in plant and animal breeding thanks to user-friendly platforms such as R. Among such software one of the most recent and popular is the sommer package. In this short communication we discuss the update of the package that is able to run multivariate mixed models with multiple random effects and different covariance structures at the level of random effects and trait-to-trait covariance along with other functionalities for genetic analysis and field trial analysis to enhance the genome-assisted prediction capabilities of researchers.