In lumi, the data was transformed (variance-stabilizing transformation (VST)) [ 49] and normalized (robust spline normalization (RSN)) [ 48], resulting in log-transformed normalized data.
In a next step, the data was transformed using either log2-transformation (log) or variance-stabilizing transformation (vst) [ 9].
N2 fixation activity data was transformed by square root transformation to permit parametric tests.
Data was transformed by variance stabilization transformation (VST) [ 13] then normalized by robust spline normalization (RSN) [ 14].
The data was transformed by a Variance-Stabilizing Transformation (VST) package [ 38] and normalized by a Robust Spline Normalization (RSN) package [ 38].
As such, the data was transformed using a log10 + 1 transformation, which yielded a normal distribution.
If data for a metabolite were skewed less upon natural log transformation, then the metabolite data was transformed and used for all subsequent analysis.
Each participant's 3D structural image (coregistered to the functional data) was transformed, via a 12-parameter affine transformation, to fit it to a Talairach template (i.e., the Colin-brain template), and then the t-value matrix was transformed to Talairach space based on structural image transformation parameters.
As this was a transformative mixed method study, the qualitative data was transformed into quantitative data so that it was integrated at the analysis stage.
Wherever necessary and to ensure normality of residuals was satisfied, data was transformed prior to analysis using Box-Cox power transformations [ 46], i.e. x' = (xp –1)/p, where p is the power maximizing normality likelihood obtained with the 'bcPower' function from the 'car' package in R. Visual inspection of the residuals indicated no violation of assumptions of homoscedasticity.
Prior to eQTL analysis for each gene expression probeset the data was transformed into a normal distribution using an inverse quantile normal transformation.
