When should you use variance stabilization transformed data?
In applied statistics, a variance-stabilizing transformation is a data transformation that is specifically chosen either to simplify considerations in graphical exploratory data analysis or to allow the application of simple regression-based or analysis of variance techniques.
What happens to mean when you multiply by a constant?
So to summarize, if we multiply our data set by a constant value or divide our data set by a constant value, then the mean, median, mode, range, and IQR will all be scaled by the same amount.
How to calculate a variance stabilizing transformation ( VST )?
This function calculates a variance stabilizing transformation (VST) from the fitted dispersion-mean relation(s) and then transforms the count data (normalized by division by the size factors or normalization factors), yielding a matrix of values which are now approximately homoskedastic (having constant variance along the range of mean values).
Which is the best function for variancestabilizingtransformation?
The more the size factors differ, the more residual dependence of the variance on the mean will be found in the transformed data. rlog is a transformation which can perform better in these cases. As shown in the vignette, the function meanSdPlot from the package vsn can be used to see whether this is a problem.
How does variancestabilizingtransformation return a deseqdataset matrix?
varianceStabilizingTransformation returns a DESeqTransform if a DESeqDataSet was provided, or returns a a matrix if a count matrix was provided. Note that for DESeqTransform output, the matrix of transformed values is stored in assay (vsd). getVarianceStabilizedData also returns a matrix.
How is the variance of a deseqtransform calculated?
Note that for DESeqTransform output, the matrix of transformed values is stored in assay (vsd) . getVarianceStabilizedData also returns a matrix. For each sample (i.e., column of counts (dds)), the full variance function is calculated from the raw variance (by scaling according to the size factor and adding the shot noise).