Introduction to the rrBLUP Package in R for Genomewide Selection Webinar
Presenter: Amy Jacobson
Part 1 - Downloading the loading the sample files
Part 2 - Imputing missing markers using A.mat()
Part 3 - Defining the training and validation populations
Part 4 - Running mixed.solve() and determining accuracy of predictions
Full webinar
About the Webinar
This webinar focuses on genomic selection in R using the rrBLUP package. Through this webinar you will learn to generate a training population, impute missing markers, estimate marker effects and determine the correlation accuracy.
Learning Objectives
- Download the package and load in the example files
- Define training and validation populations
- Impute missing markers using the A.mat command
- Run mixed.solve and determine accuracy of predictions
Software Downloads
R: free software environment for statistical computing and graphics
About the Presenter
Amy Jacobson is a PhD student at the University of Minnesota advised by Dr. Rex Bernardo. Amy received her bachelor’s degree in plant science from Cornell University in 2011. She is currently researching improving accuracy of genomic selection in maize biparental populations.
About Plant Breeding and Genomics
We are an web-base extension organization committed to free sharing of ideas, techniques, and computational tools for the advancement of agriculture and global food security. Visit our website to learn about upcoming events and watch all of our recorded webinars.
Funding Statement
Development of this page was supported in part by the National Institute of Food and Agriculture (NIFA) Solanaceae Coordinated Agricultural Project, agreement 2009-85606-05673, administered by Michigan State University. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the United States Department of Agriculture.
Introduction to the rrBLUP Package in R for Genomewide Selection by Amy Jacobson is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.
Attachment | Size |
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code.txt | 2.61 KB |
snp.txt | 275.15 KB |
traits.txt | 1.23 KB |
Introduction to Genomic Selection in R.pdf | 902.17 KB |