runClustering: Cluster 2D data

In karyotapR: DNA Copy Number Analysis for Genome-Wide Tapestri Panels

Cluster 2D data

Description

Clusters data using dbscan method and saves cluster assignments for each cell barcode to colData. Generally used to assign clusters to UMAP projection after PCA and UMAP dimensional reduction.

Usage

runClustering(
  TapestriExperiment,
  alt.exp = "alleleFrequency",
  dim.reduction = "UMAP",
  eps = 0.8,
  dim.1 = 1,
  dim.2 = 2,
  ...
)

Arguments

TapestriExperiment	TapestriExperiment object
alt.exp	Character, altExp slot to use. NULL uses top-level/main experiment. Default "alleleFrequency".
dim.reduction	Character, reduced dimension data to use. Default "UMAP".
eps	Numeric, dbscan eps parameter. Lower to increase cluster granularity. See dbscan::dbscan(). Default 0.8.
dim.1	Numeric, index of data dimension to use. Default 1.
dim.2	Numeric, index of data dimension to use. Default 2.
...	Additional parameters to pass to dbscan::dbscan().

Value

TapestriExperiment object with updated colData containing cluster assignments.

See Also

dbscan::dbscan()

Examples

tap.object <- newTapestriExperimentExample() # example TapestriExperiment object
tap.object <- runPCA(tap.object, alt.exp = "alleleFrequency")
tap.object <- runUMAP(tap.object, pca.dims = 1:3)
tap.object <- runClustering(tap.object, dim.reduction = "UMAP", eps = 0.8)

karyotapR documentation built on Sept. 8, 2023, 5:07 p.m.