posmeansGG {gaga} | R Documentation |
Computes posterior means for the gene expression levels using a GaGa or MiGaGa model.
posmeansGG(gg.fit, x, groups, sel, underpattern)
gg.fit |
GaGa or MiGaGa fit (object of type |
x |
|
groups |
If |
sel |
Numeric vector with the indexes of the genes we want to
draw new samples for (defaults to all genes). If a logical vector is
indicated, it is converted to |
underpattern |
Expression pattern assumed to be true (defaults to
last pattern in |
The posterior distribution of the mean parameters actually depends on
the gene-specific shape parameter(s), which is unknown. To speed up
computations, a gamma approximation to the shape parameter posterior
is used (see rcgamma
for details) and the shape parameter is
fixed to its mode a posteriori.
Matrix with mean expression values a posteriori, for each selected gene and each group. Genes are in rows and groups in columns.
David Rossell
Rossell D. GaGa: a simple and flexible hierarchical model for microarray data analysis. http://rosselldavid.googlepages.com.
fitGG
for fitting GaGa and MiGaGa models,
parest
for computing posterior probabilities of
each expression pattern.