Description Usage Arguments Value Author(s) See Also Examples
In cases where multiple models are simultaneously evaluated in the 'getLikelihoods' function, the posterior likelihoods for each model in which one condition is greater than another can be summed to give the marginal likelihood of (directed) difference for all biomolecular events (i.e., data rows).
1 | marginalisePairwise(cD, greaterThan, lessThan)
|
cD |
A |
greaterThan |
A defined group name (or vector of group names) to identify in the
'@groups' slot of the |
lessThan |
A defined group name (or vector of group names) to identify in the
'@groups' slot of the |
A vector of marginal posterior likelihoods defining the probability that the two group identifiers are (directionally) different for each row of the data.
Thomas J. Hardcastle
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | # load test data
data(simData)
# Create a {countData} object from test data, supposing that there are
# multiple experimental groups present.
replicates <- c("simA", "simA", "simB", "simC", "simC", "simD", "simE", "simE", "simF", "simG")
CD <- new("countData", data = simData, replicates = replicates)
CD <- allModels(CD)
# The total number of models generated is high.
length(CD@groups)
# Priors and likelihoods acquired through standard means.
## Not run: CD <- getPriors(CD, cl = cl)
## Not run: CD <- getLikelihoods(CD, cl = cl)
# Marginal likelihood that 'simA' condition is greater than 'simD' group
# for each row of the data.
## Not run: marginalisePairwise(CD, "simA", "simD")
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