GSEA.mean.t {SAGx} | R Documentation |
Based on a list of gene sets, e.g. pathways, in terms Affymtrix identifiers, these sets are ranked with respect to regulation as measured by an effect in a linear model using the SAM statistic.
GSEA.mean.t(data = X, samroc = samroc.res, probeset = probeset, pway = kegg, absolute = TRUE, two.side = FALSE, cutoff = c(5,Inf), B = 1000, smooth = FALSE)
data |
data matrix |
samroc |
an object of class samroc.result |
probeset |
the Affymetrix identifiers |
pway |
a list of pathways or gene sets |
absolute |
if TRUE the absolute value of the absolute value of the samroc test statistic is used. Currently this is the only option |
two.side |
if TRUE a two-sided test is performed. Currently only one-sided test allowd |
cutoff |
Gene sets with the number of members not falling within the interval given by cutoff are excluded |
B |
the number of permutations |
smooth |
if TRUE smoothing of SEs is performed. Currently this is not permitted |
A vector of p-values
Experimental function
Per Broberg
Tian, Lu and Greenberg, Steven A. and Kong, Sek Won and Altschuler, Josiah and Kohane, Isaac S. and Park, Peter J. (2005) Discovering statistically significant pathways in expression profiling studies, PNAS Vol. 102, nr. 38, pp. 13544-13549