IPA-Defining the Reference Set

Defining the Reference Set    

This parameter enables you to specify which molecule set (Reference Set) should be viewed as the complete universe when ranking the statistical significance of Functions and Canonical Pathways.  In Functions and Canonical Pathways, the high-level functions and canonical pathways most relevant to your input genes are identified, then displayed in order of statistical significance.  In calculating which functions and pathways are significant, IPA compares the functions associated with your functional analysis molecules to functions associated with all molecules in the reference set.

Why This Parameter is Important

The statistical significance (p-values) of the biological functions and pathways returned in Functional Analysis is determined by calculating the extent to which the functions associated with your dataset deviate from what was expected by chance alone. The significance value indicates to what degree there are more functional analysis molecules implicated in the given function or pathway, compared to what would be expected by random chance.

In order to define what would be expected by chance, the application needs to know what to use as a reference - essentially, what group of molecules to use as the complete set of molecules when calculating p-values.

Default Settings

IPA has three types of reference sets that can be used for your analysis: the Ingenuity Knowledge Base, Specific Array Platforms, or your dataset. IPA makes an initial selection of this parameter for you by making reasonable assumptions about your dataset.

• If you have used one of the supported array platforms, IPA will then use that platform as the Reference Set.

• If you have not used one of the array platforms above, the default reference set is the Ingenuity Knowledge Base so that you can ensure consistency across different datasets and analyses.

• You can also decide to use your dataset as the reference set, if it is sufficiently large (>90,000 identifiers).