Processes | Annotation Analysis | Significance Variables

Significance Variables
Specify variables from the Input SAS Data Set that contain continuous significance measures or numeric binary indicators created from continuous significance measures.
Common continuous measures to use are t-statistics , -log 10 ( p -values), or p-values . The significance variables specified here should all be of the same kind (for example. all t -statistics or all -log 10 ( p -values)). Basic characteristics or uses of each are as follows:
T -statistics are recommended for simultaneously testing both up- and down-regulation.
P -value-based measures only screen for absolute significance.
-Log 10 ( p -values) are preferred to p -values for Cochran-Armitage and PAGE tests because they have more compatible sampling distributions .
If binary indicators are specified here, you must specify a value in the Significance Variable Cutoff for Fisher Exact Tests field on the Analysis tab. For example, if you specify one or more binary indicators in which 0 represents non-significance and 1 represents significance, you must specify a value greater than 0 and less than 1 as your Significance Variable Cutoff for Fisher Exact Tests .
To Specify Significance Variables:
The Available Variables field is populated with variables from the specified data set.
Highlight a single variable, or hold down Ctrl while left-clicking on multiple variables, from the Available Variables field.