The terpenoid synthase subfamilies established that more variance is explained when BPPs are encoded compared to the commonly used binary encoding which does not integrate physicochemical aspects of protein sequences.
Of all dairy traits, only fat percent was significant in both the upstream and downstream classes, although there was a trend for the other annotations to explain more of the variance when compared to the random intergenic set for the traits fat percent, milk production and protein percent (Table 5, Figure 3).
Figures 5 and 6 illustrate the change in the estimated variance when more samples are added to the analysis.
Group differences were analysed using nonparametric tests for continuous parameters (Mann–Whitney U test when comparing two groups and Kruskal Wallis analysis of variance when more than two groups were compared).
This is a consequence of the increased sampling variance when estimating more parameters [see [ 22, 11]].
Results suggest that the IBD matrix explained substantially more variance than the IBS matrix, when they were fitted together in the model.
The estimates of the variance components in Table 3 show that the IBD matrix explained much more variance than the IBS matrix when they were fitted together in the model.
Generally, in headache studies, only one of a family should be selected, because members of families are similar genetically, share their environment and have common lifestyles, effectively reducing variance when two or more are included.
Data comparisons were performed using the Student's t test when two groups were compared or one-way ANOVA analysis of variance when three or more groups were analyzed.
Differences between means in continuous variables were measured by: the Mann–Whitney U test when the variables were two and unrelated, the Wilcoxon signed-rank test when the variables were two and related, and analysis of variance when we had more than two unrelated variables.
