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A design matrix was generated using the GLM tool in FSL.
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Data were analyzed using the GLM or Kruskal Wallis and Dwass-Steel-Critchlow-Fligner tests.
Data were fitted using the glm function of the R package [24].
Data were then evaluated using the GLM in a random effects analysis.
All GLM analyses were performed using the glm procedure in R (version 2.10.1, [ 58]).
Using the GLM, we assessed complementary expression patterns between paralogs.
GLMs were fitted using the glm function, while GLMMs were fitted using the glmer function in the lme4 package [ 28].
We implemented the model using the glm function in R (R Development Core Team 2008).
The analysis were implemented using the GLM function in R [ 9].
The morphological value of each trait was normalized using the GLM (see Methods).
Fractional logit regression models were estimated using the glm function and the sandwich function [ 19].
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