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Counts were transformed through variance stabilizing transformation (VST) using the DESeq package [ 19] in R (www.r-project.org) according to the DESeq reference manual.
In fact, the square root transform is the variance stabilizing transformation of Poisson distributed variables and is therefore the "natural" choice for count variables[ 9].
Alternative microRNA expression similarity metrics including Euclidean distance (supplementary fig. S3, Supplementary Material online), Pearson's correlation between log2-transformed values, and values normalized by variance stabilizing transformation (Anders and Huber 2010) generate consistent results (data not shown).
Genes were grouped according to their expression profiles by transforming the expression data into moderate fold change estimates using a variance stabilizing transformation [ 37].
We tried to use variance stabilizing transformation (VSN) for normalization as well.
Microarray data were normalized using the lumi package in R, using the variance stabilizing transformation (VST) of the package and robust spline normalization (RSN).
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Using the lumi package, we implemented various types of background correction (e.g. 'none'bgAdjust'st'forcePositiveivarianceriance stabilization ('vst' (variance-stabilizing transformation), 'log2', 'cubicRoot') and normalization.
In lumi, the data was transformed (variance-stabilizing transformation (VST)) [ 49] and normalized (robust spline normalization (RSN)) [ 48], resulting in log-transformed normalized data.
Subsequently, signal intensities were VST-transformed (variance-stabilizing transformation) and RSN-normalized (robust spline normalization) using the Lumi package in R. Post-processing and statistical analysis of microarray data was carried out in Matlab.
For clustering and heatmaps of expression values, DESeq-normalized data were prior transformed with the Variance-stabilizing transformation (VST) as described by Anders and Huber [ 105].
The data was transformed by a Variance-Stabilizing Transformation (VST) package [ 38] and normalized by a Robust Spline Normalization (RSN) package [ 38].
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