JSM 2013 Home
Online Program Home
My Program

Abstract Details

Activity Number: 644
Type: Contributed
Date/Time: Thursday, August 8, 2013 : 8:30 AM to 10:20 AM
Sponsor: Section on Nonparametric Statistics
Abstract - #309648
Title: Implementation of Parametric and Nonparametric Models for Genomic-Assisted Selection in Plant Breeding
Author(s): Reka Howard*+ and Alicia Carriquiry and William Beavis
Companies: Iowa State University and Iowa State University and Iowa State University
Keywords: parametric, nonparametric, genomic selection, prediction

Genomic selection (GS) has become an important tool in breeding. Accordingly, statistical approaches for genomic assisted prediction have also evolved. Meuwissen et al. (2001) proposed parametric methods for GS. Nonparametric methods for GS, which require fewer assumptions than parametric methods, can handle the multiplicity of potential interactions across the genome. In this presentation, we implement some of the parametric and nonparametric methods for GS using simulated data containing phenotypic and marker information on F2 and BC populations. We consider marker data with and without interactions, and we compare the performance of the methods for predicting the genetic value for individuals in the plant breeding populations. The performance of the different methods is illustrated by comparing the accuracy of prediction. We show the advantage of using nonparametric models when interaction presents.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2013 program

2013 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

ASA Meetings Department  •  732 North Washington Street, Alexandria, VA 22314  •  (703) 684-1221  •  meetings@amstat.org
Copyright © American Statistical Association.