associatePosteriors {clusterSeq} | R Documentation

## Associates posterior likelihood to generate co-expression dissimilarities between genes

### Description

This function aims to find pairwise dissimilarities between genes. It does this by comparing the posterior likelihoods of patterns of differential expression for each gene, and estimating the likelihood that the two genes are not equivalently expressed.

### Usage

    associatePosteriors(cD, maxsize = 250000, matrixFile = NULL)

### Arguments

`cD` | A `countData` object containing posterior likelihoods of differential expression for each gene.
`maxsize` | The maximum size (in MB) to use when partitioning the data.
`matrixFile` | If given, a file to write the complete (gzipped) matrix of pairwise distances between genes. Defaults to NULL.

### Details

In comparing two genes, we find all patterns of expression considered in the '@groups' slot of the 'cD' (`countData`) object for which the expression of the two genes can be considered monotonic. We then subtract the sum the posterior likelihods of these patterns of expression from 1 to define a likelihood of dissimilarity between the two genes.

### Value

A data.frame which for each gene defines its nearest neighbour of higher row index and the dissimilarity with that neighbour.

### Author(s)

Thomas J. Hardcastle

### See Also

`makeClusters` `makeClustersFF` `kCluster`

### Examples

    # load in analysed countData (baySeq package) object
    library(baySeq)
    data(cD.ratThymus, package = "clusterSeq")

    # estimate likelihoods of dissimilarity on reduced set
    aM <- associatePosteriors(cD.ratThymus[1:1000,])

[Package clusterSeq version 1.18.0 Index]