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Percentage values were square root transformed for variance stabilization.
Fold change was log transformed for variance stabilization and a single overall p-value that tests if there is a difference between treatments was generated.
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Data for transcript accumulation were cube-root transformed for normality and variance homogeneity.
Data on proportion detected images were arcsine transformed for normality and homogeneity of variances, and data on time to detection were square root transformed prior to analyses.
Raw data for each variable were then transformed for Levene's Test following the procedure described by Plavcan and Cope [36] to compare distribution variances between taxa.
Data were not transformed for QRA as it is a non-parametric test that makes no assumptions regarding normality of distribution or variance homogeneity.
Transformed estimates were back transformed for presentation.
The latter is the variance stabilizing transform for Poisson data.
Goodness of fit for the transformed variance to mean relationship and the model CDF were further assessed by analyses of residuals.
The signal was transformed and variance stabilized by log2 signal +16).
The data were transformed by variance stabilization and quantile normalized.
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CEO of Professional Science Editing for Scientists @ prosciediting.com