Data transformations such as log transformation are often used to improve normality.
While SWISS does not necessarily account for the full range of potential biases, it does allow for decisions about data transformations such as gene filtering to be made independently for each data source.
Data transformations such as taking logarithms may be appropriate and any missing values can be imputed using regression techniques.
As we demonstrated, a variety of data transformations such as log-transformation, arcsine transformation and others can sometimes be used to obtain normal distributions in some cases when the underlying variable is non-normally distributed.
The methods for reducing the complexity and downsizing the data scale to make the data useful for data analysis part are usually employed in the transformation, such as dimensional reduction, sampling, coding, or transformation.
Generally, it is best to work with raw (untransformed) data, although transformations such as percent of baseline are commonly needed in reports.
This paper also discusses important issues of model transformation, such as semantics mapping, data type mappings and transformation rules.
Our data demonstrate that Rac regulates important effectors of NPM ALK-induced traNPM ALK-inducedh as Erk1/2, p38 and Aktransformation
He called it a transformation "such as we have never seen before".
And if more complex transformation such as three-order polynomial transformation is used, more general distortions can also be removed.
