Exact(2)
In a next step, the data was transformed using either log2-transformation (log) or variance-stabilizing transformation (vst) [ 9].
As such, the data was transformed using a log10 + 1 transformation, which yielded a normal distribution.
Similar(58)
The data were transformed using the variance stabilization transformation (VST) [37] and normalized using the robust spline normalization (RSN) [36].
Due to non-normal distributions and in order to test for significance, the data were transformed using the square-root transformation to normalize the distribution.
If the counts were small (<10), tended toward a Poisson distribution and did not satisfy normality, the data were transformed using the square root transformation, and ANOVAs were performed on transformed data [ 31].
In order to achieve normality the data were transformed using the natural logarithm (ln) transformation.
The data are transformed using modeling techniques and the resulting uncertainty is quantified through sensitivity analyses before making a recommendation regarding reimbursement.
For statistical analysis, the results were expressed as a proportion and the data were transformed using Arc Sine.
The data were transformed using the weighted least squares method.
The data were transformed using Variance Stabilization (VST) (Lin et al., 2008) and normalized using quantile normalization.
The data were transformed using an automatic algorithm contained in the SeqDisplyer program into "bands" files.
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