Contents - Index

Generating the (marker-by-environment) table of marker-effects


Previous: QTL identification based on phenotypic data from multiple environments.


Under the main menu VBV Biplot, click Covariate-effect biplot, and select r-Matrix (or b-matrix). An input box will appear, asking for how many markers are there in the combined two-way table. In our case of the barley H-T mapping data, it is 127:


GGEbiplot detects that there are a total of 152 columns, and thereby use the first 127 columns as explanatory variables and the rest 25 response variables to generate a table of 127 * 25 correlations, each of which is the Pearson correlation between the relevant marker and the target trait in the relevant environment. When this is done, the researcher will be noticed that the data structure is changed:


(Note: In the current version of GGEbiplot, the data format is more flexible. When the function is invoked, a form like the one will appear and the user is asked to separate the variables into N explanatory variables and the M response variables.)


Next: Screening for relevant markers