Heather L. Merk, The Ohio State University
This workshop/webinar module focuses on estimating trait heritability on a line mean basis and estimating best linear unbiased predictors (BLUPs) for traits using the tomato fruit shape, size, color, and quality data collected for SolCAP as an example.
After watching this webinar, you should be able to:
Supplemental data and script files are provided in the "Attachments" section at the bottom of the page.
IMPORTANT NOTE: The code provided has been tested for 2.x of R. There are issues with the code for version 3.0. See the bottom of the page about updates to LME4.
Experimental design, data collection, obtaining sample data from SolCAP, getting started with R software for the analysis, setting the working directory.
Importing and checking the data, visualizing the data, setting the model with nesting and interactions, treating main effects as fixed or random, installing and loading the lme4 package in R, calculating the variance components, estimating heritability.
Estimating BLUPs (Best Linear Unbiased Predictors) for each line, selections based on BLUPs.
There have been several “Major User” changes to lme4 since this webinar was presented. Some of these changes affect the script provided with the webinar (below), and result in an error being generated. The supplemental file "CHANGES_to_lme4_V2.0.pdf" provided under attachments describes some of these changes and additional R code that will be needed to analyze the data provided.
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.
TBRT2011Script.txt (1.67 KB)
TBRTQuality.csv (42.56 KB)
CHANGES_to_lme4_V2.0.pdf (102.71 KB)