clusterExpressionPatterns | R Documentation |
Cluster genes in clusters that have similar expression patterns
along all lineages in the trajectory. By default, this function uses the
clusterExperiment
package to do the clustering. If another clustering
method is of interest, one can extract fitted values to use for clustering,
see details in the vignette.
## 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,
...
)
models |
The fitted GAMs, typically the output from
|
nPoints |
The number of points to use for clustering the expression patterns. |
genes |
A numerical or character vector specifying the genes from
|
reduceMethod |
Dimensionality reduction method used before running the
clustering methods. Passed to |
nReducedDims |
Number of dimensions kept after |
minSizes |
Minimum size of clusters.
Passed to |
ncores |
Number of cores to use. Passed to
|
random.seed |
Passed to |
verbose |
Passed to |
... |
Additional arguments to be passed to
|
This method adopts the RSEC
function from the clusterExperiment package to perform consensus clustering.
A list containing the scaled fitted values yhatScaled
(for
plotting) and a clusterExperiment
object, containing the
clustering results.
## Not run:
data(gamList, package = "tradeSeq")
clusterExpressionPatterns(models = gamList, nPoints = 200, genes = seq_len(11),
verbose = FALSE)
## End(Not run)
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