spatialEnhance {BayesSpace} | R Documentation

## Enhance spot resolution

### Description

Enhanced clustering of a spatial expression dataset to subspot resolution.

### Usage

    spatialEnhance(
      sce,
      q,
      platform = c("Visium", "ST"),
      use.dimred = "PCA",
      d = 15,
      init = NULL,
      init.method = c("spatialCluster", "mclust", "kmeans"),
      model = c("t", "normal"),
      nrep = 2e+05,
      gamma = NULL,
      mu0 = NULL,
      lambda0 = NULL,
      alpha = 1,
      beta = 0.01,
      save.chain = FALSE,
      chain.fname = NULL,
      burn.in = 10000,
      jitter_scale = 5,
      jitter_prior = 0.3,
      verbose = FALSE
    )

### Arguments

`sce` | A SingleCellExperiment object containing the spatial data.
`q` | The number of clusters.
`platform` | Spatial transcriptomic platform. Specify 'Visium' for hex lattice geometry or 'ST' for square lattice geometry. Specifying this parameter is optional when analyzing SingleCellExperiments processed using `readVisium`, `spatialPreprocess`, or `spatialCluster`, as this information is included in their metadata.
`use.dimred` | Name of a reduced dimensionality result in `reducedDims(sce)`. If provided, cluster on these features directly.
`d` | Number of top principal components to use when clustering.
`init` | Initial cluster assignments for spots.
`init.method` | If `init` is not provided, cluster the top `d` PCs with this method to obtain initial cluster assignments.
`model` | Error model. ('normal' or 't')
`nrep` | The number of MCMC iterations.
`gamma` | Smoothing parameter. (Values in range of 1-3 seem to work well.)
`mu0` | Prior mean hyperparameter for mu. If not provided, mu0 is set to the mean of PCs over all spots.
`lambda0` | Prior precision hyperparam for mu. If not provided, lambda0 is set to a diagonal matrix 0.01 I.
`alpha` | Hyperparameter for Wishart distributed precision lambda.
`beta` | Hyperparameter for Wishart distributed precision lambda.
`save.chain` | If true, save the MCMC chain to an HDF5 file.
`chain.fname` | File path for saved chain. Tempfile used if not provided.
`burn.in` | Number of iterations to exclude as burn-in period. The MCMC iterations are currently thinned to every 100; accordingly `burn.in` is rounded down to the nearest multiple of 100.
`jitter_scale` | Controls the amount of jittering. Small amounts of jittering are more likely to be accepted but result in exploring the space more slowly. We suggest tuning `jitter_scale` so that Ychange is on average around 25%-40%.
`jitter_prior` | Scale factor for the prior variance, parameterized as the proportion (default = 0.3) of the mean variance of the PCs. We suggest making `jitter_prior` smaller if the jittered values are not expected to vary much from the overall mean of the spot.
`verbose` | Log progress to stderr.

### Details

The enhanced `SingleCellExperiment` has most of the properties of the input SCE - `rowData`, `colData`, `reducedDims` - but does not include expression data in `counts` or `logcounts`. To impute enhanced expression vectors, please use [enhanceFeatures()] after running `spatialEnhance`.

The `colData` of the enhanced `SingleCellExperiment` includes the following columns to permit referencing the subspots in spatial context and linking back to the original spots:

- `spot.idx`: Index of the spot this subspot belongs to (with respect to the input SCE).

- `subspot.idx`: Index of the subspot within its parent spot.

- `spot.row`: Array row of the subspot's parent spot.

- `spot.col`: Array col of the subspot's parent spot.

- `row`: Array row of the subspot. This is the parent spot's row plus an offset based on the subspot's position within the spot.

- `col`: Array col of the subspot. This is the parent spot's col plus an offset based on the subspot's position within the spot.

- `imagerow`: Pixel row of the subspot. This is the parent spot's row plus an offset based on the subspot's position within the spot.

- `imagecol`: Pixel col of the subspot. This is the parent spot's col plus an offset based on the subspot's position within the spot.

### Value

Returns a new SingleCellExperiment object. By default, the `assays` of this object are empty, and the enhanced resolution PCs are stored as a reduced dimensionality result accessible with `reducedDim(sce, 'PCA')`.

### See Also

`spatialCluster` for clustering at the spot level before enhancing, `clusterPlot` for visualizing the cluster assignments, `enhanceFeatures` for imputing enhanced expression, and `mcmcChain` for examining the full MCMC chain associated with the enhanced clustering. .

### Examples

    set.seed(149)
    sce <- exampleSCE()
    sce <- spatialCluster(sce, 7, nrep=100, burn.in=10)
    enhanced <- spatialEnhance(sce, 7, nrep=100, burn.in=10)

[Package BayesSpace version 1.2.1 Index]