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The average trait value of each accession was used in data analyses of GWAS.
The evolutionary response is symbolized as R, and is calculated as the average trait value in the current generation (offspring) subtracted from the average trait value in the previous generation (parents).
Both figures plot average trait value between the two parents (mid-parent trait value) and the trait values for each resulting offspring.
We calculated the average phenotypic score and variance associated with it in this generation and determined the evolutionary response (R) to selection as the average trait value in the current generation subtracted from the average trait value in the previous generation prior to selection.
At this point, students make a quantitative prediction about what the average trait value should be in the next generation according to the theory of evolution by natural selection.
Note that the inclusion of random environmental effects need not change the average trait value across generations; however, the heritability is drastically reduced leading to a dampened response to selection.
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We show how using simple regression models in conjunction with external data such as average trait values can improve the power of genome-wide association studies.
Average trait values of four environments were used.
If the observed value for a node lands in the p = 0.05 tails of the null distribution, the trait has significant signal at that node and all descendant taxa have average trait values more similar than expected.
By manipulating the nutritional environment that populations experienced, we have documented a shift in average trait values but not the relationships between traits in a way that is consistent with the predictions of short term or weak selection.
Average trait values for each genotypic class (i.e., 1, 3, 6, or 12) were also used as observed values to test for non-additivity against a null model.
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