BayesKnockdown.es {BayesKnockdown} | R Documentation |
Calculates posterior probabilities for an ExpressionSet object by defining one feature as the predictor. Each other feature in the ExpressionSet is is then used as a response variable and posterior probabilities are calculated, incorporating prior probabilities potentially unique to each response variable.
BayesKnockdown.es(es, predFeature, prior = 0.5, g = sqrt(dims(es)[2,1]))
es |
An ExpressionSet object with |
predFeature |
The name of the feature to use as the predictor. |
prior |
Prior probabilities for the outcome variables. Defaults to 0.5 for all variables. |
g |
The value to use for Zellner's g-prior. Defaults to the square root of the number of observations. |
A vector of p-1
posterior probabilities indicating
the probability of a relationship between the predictor variable
and each outcome variable.
library(Biobase); data(sample.ExpressionSet); subset <- sample.ExpressionSet[1:10,]; BayesKnockdown.es(subset, "AFFX-MurIL10_at");