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]