BayesKnockdown {BayesKnockdown} | R Documentation |
Calculates posterior probabilities for edges from a knocked-down gene to each of a set of potential target genes. More generally, it calculates posterior probabilities between a single predictor variable and each of a set of response variables, incorporating prior probabilities potentially unique to each response variable.
BayesKnockdown(x, y, prior = 0.5, g = sqrt(length(x)))
x |
|
y |
Outcome matrix: |
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
posterior probabilities indicating
the probability of a relationship between the predictor variable
and each outcome variable.
n <- 100; p <- 10; x <- rnorm(n); y <- matrix(nrow=p, data=rnorm(n*p)); y[3,] <- y[3,] + 0.5*x; BayesKnockdown(x, y);