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To assess the stability of our results, we produced power calculation through simulation process: 100 new dependant variables were generated and 100 new mixed model calculations were computed thus proportion of success (p value equal or inferior to 0.05) defines as power.
All mixed model calculations were performed with ASReml [ 50].
The GRAMMAR approach allows genome-wide mixed model calculations to be computed on a reasonable timescale.
All mixed-model calculations were performed with ASReml release 2.0 [ 70].
Although the primary analyses proposed a full information mixed model approach, to be conservative, the power calculations were also examined based on a two-group comparison of endpoint means (differences in means), with possible attrition.
Therefore, we first approximately calculated the variance components without considering a QTL effect and then imposed the estimates of variance components on the mixed model equation, which does not need an iterative calculation and thus reduces computational time.
If no dropouts occur, the estimate of the difference between treatment and control arms from this mixed model will yield identical results to the simple calculation of a difference in means.
Calculation of the FDRs for the mixed model approach was carried out with scripts modified from the Cyber-T source code.
The best linear unbiased predictor (BLUP) calculation was implemented using a PROC MIXED model, with genotype, location, genotype by location, and replications as random effects [ 47].
Calculations were done using the PROC MIXED model of the SAS analytical system (version 9.2).
The analysis of variance calculations for sums of squares in the mixed model ANOVA are identical to those for the fixed ANOVA model.
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