The
P-Value Combination
process combines p-values from multiple units (such as
SNPs
or genes) into a single p-value for each group (such as gene or pathway, respectively) that comprises those units. For genome-wide association studies (
GWAS
), this process can be performed twice: once to combine SNP p-values into a single gene p-value, then a second time to combine gene p-values into a pathway p-value.
One
Input Data Set
, containing the
p
-values of an arbitrary set of features (for example, genes,
probesets
,
exons
, markers) is required for this process.
A
second, optional, data set
is the
Annotation Data Set
. This data set contains information, such as gene identity or chromosomal location, for each of the markers. An
annotation data set
is required only if the input data set does not contain the relevant annotation information.
Running the
P-Value Combination
process results in the generation of one output data set with two columns. One column lists the name for each of the units (genes, SNPs, and so on) in the experiment. The second column lists the
p
-values combined across each of the units.