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"These methods have power, and they are certainly an advance in the way we can evaluate ideas.
Both methods have power primarily to detect candidates of recent domestication events but of different types of selection.
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Our experimental results demonstrate the effectiveness of the proposed method; the method has power overheads of less than 1% compared with designs that do not support a deadlock removal method.
This sample size was chosen because it was felt to be large enough for large sample properties to hold, but not so large that both methods would have power too high for comparison.
Power simulations have shown that the new methods have comparable power with a popular method known to work well in low-dimensional situation but the new methods have shown enormous advantage when the dimension is large.
In the presence of outliers, the proposed nonparametric methods have better power than their parametric counterparts.
As presented in table 6, all the methods have increased power with increased r2.
Looking at the rows of scatterplots corresponding to FM and GMRE, the points fall on or above the diagonal, indicating that these methods have higher power than the other approaches over all scenarios investigated.
The reason that many methods fail to report this QTL is that these methods have limited power in detecting non-additive effects.
Statistical methods have better power while there is an "a priori" hypothesis as shown in the study of summer excess of leukaemia [ 10].
With a marker interval d=62.5 kb, which is approximately the resolution obtained when genotyping mammals with 50 k SNP arrays, all methods have low power <10%.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com