marginaliseEqual {baySeq} | R Documentation

## Computes marginal likelihoods that two replicate groups are equal.

### Description

In cases where multiple models are simultaneously evaluated in the 'getLikelihoods' function, the posterior likelihoods for each model in which two conditions are equivalent can be summed to give the marginal likelihood of equivalence for all biomolecular events (i.e., data rows).

### Usage

    marginaliseEqual(cD, r1, r2)

### Arguments

`cD` | A `countData` object with evaluated posterior likelihoods in the '@posteriors' slot.
`r1` | A defined group name to identify in the '@groups' slot of the `countData` object 'cD'.
`r2` | A defined group name to identify in the '@groups' slot of the `countData` object 'cD'.

### Value

A vector of marginal posterior likelihoods defining the probability that the two group identifiers are equal for each row of the data.

### Author(s)

Thomas J. Hardcastle

### See Also

`allModels` `marginalisePairwise`

### Examples

    # 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' and 'simD' replicate groups are equal
    # for each row of the data.

    ## Not run: marginaliseEqual(CD, "simA", "simD")

[Package baySeq version 2.16.0 Index]