clusterExpressionPatterns {tradeSeq} | R Documentation

## Cluster gene expression patterns.

### Description

Cluster genes in clusters with similar expression patterns along the trajectory.

### Usage

    ## S4 method for signature 'SingleCellExperiment'
    clusterExpressionPatterns(models, nPoints,
      genes, reduceMethod = "PCA", nReducedDims = 10, minSizes = 6,
      ncores = 1, random.seed = 176201, verbose = TRUE, ...)

    ## S4 method for signature 'list'
    clusterExpressionPatterns(models, nPoints, genes,
      reduceMethod = "PCA", nReducedDims = 10, minSizes = 6,
      ncores = 1, random.seed = 176201, verbose = TRUE, ...)

### Arguments

`models` | The list of GAMs, typically the output from `fitGAM`.
`nPoints` | The number of points to use for clustering the expression patterns.
`genes` | A numerical or character vector specifying the genes from `models` that should be clustered.
`reduceMethod` | Method used before running the clustering methods. Passed to `RSEC`
`nReducedDims` | Number of dimensions kept after `reduceMethod`. Passed to `RSEC`
`minSizes` | Number of dimensions kept after `reduceMethod`. Passed to `RSEC`
`ncores` | Number of cores to use. Passed to `RSEC`
`random.seed` | Passed to `RSEC`
`verbose` | Passed to `RSEC`
`...` | Additional arguments to be passed to `RSEC`.

### Details

This method adopts the `RSEC` function from the clusterExperiment package to perform consensus clustering.

### Value

A list containing the scaled fitted values `yhatScaled`(for plotting) and a `ClusterExperiment` object.

### Examples

    data(gamList, package = "tradeSeq")
    clusterExpressionPatterns(gamList, 200, seq_len(11))

[Package tradeSeq version 1.0.1 Index]