Variation explained by each experimental factor based on PERMANOVA (b).
Malone, J. et al. Modeling sample variables with an experimental factor ontology.
The rationale for the experimental factor choice, intervention design, and trial methods are discussed.
A fourth experimental factor was added to this full factorial design, which comprised the mixing of soil so as to simulate mechanical scarification in the field.
When grouping traits according to their Experimental Factor Ontology (EFO) category47, we found that loci associated with immune system disorders such as ulcerative colitis or type-1 diabetes (N = 27, OR = 4.6, resampling p < 0.001) and body measurements such as height or body mass index (N = 25, OR = 3.1, resampling p < 0.001) were the most significantly enriched (Fig. 5a).
The first experimental factor was the number of tests.
The final selection of the experimental factor and factor's levels is shown in Table 8.
The soil organic carbon contents were transformed into organic matter contents by multiplying by 1.724, which is an experimental factor, as reported by Hesse (1972).
This indicates that the extraction yield and relevant analysis items have obvious surface relationships, and interactions among each experimental factor are not significant.
The experimental plan was monofactorial and balanced, the experimental factor tested was the disinfection, and four levels and four replicates (4 × 4) were adopted.
Since previous reports [15, 27, 34, 41, 42] showed that males and females respond similarly to both the aggregation pheromone and the host plant odors, weevils' sex was not considered an experimental factor.
