mcmcChain {BayesSpace} | R Documentation

## Read MCMC chain associated with a BayesSpace clustering or enhancement

### Description

BayesSpace stores the MCMC chain associated with a clustering or enhancement on disk in an HDF5 file. The `mcmcChain()` function reads any parameters specified by the user into a `coda::mcmc` object compatible with TidyBayes.

### Usage

    mcmcChain(sce, params = NULL)

    removeChain(sce)

### Arguments

`sce` | SingleCellExperiment with a file path stored in its metadata.
`params` | List of model parameters to read

### Details

To interact with the HDF5 file directly, obtain the filename from the SingleCellExperiment's metadata: `metadata(sce)$chain.h5`. Each parameter is stored as a separate dataset in the file, and is represented as a matrix of size (n_iterations x n_parameter_indices). Parameter choices for the spot-level clustering include:

- `z` (cluster assignments)

- `weights` (w_i)

- `mu` (mean vectors)

- `lambda` (precision matrix)

- `plogLik` (pseudo-log-likelihood)

Parameter choices for the subspot-level enhanced clustering include:

- `z` (cluster assignments)

- `weights` (w_i)

- `Y` (enhanced PCs)

- `mu` (mean vectors)

- `lambda` (precision matrix)

- `Ychange` (acceptance rate for the jittering of PCs)

### Value

Returns an `mcmc` object containing the values of the requested parameters over the constructed chain.

### Examples

    set.seed(149)
    sce <- exampleSCE()
    sce <- spatialCluster(sce, 7, nrep=100, burn.in=10, save.chain=TRUE)
    chain <- mcmcChain(sce)
    removeChain(sce)

[Package BayesSpace version 1.4.1 Index]