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Perform CNV Clustering with Seurat Object

CNVcluster.Rd

The CNVcluster function performs hierarchical clustering on a genomic score matrix extracted from a Seurat object. It provides options for plotting a dendrogram, an elbow plot for optimal cluster determination, and cluster visualization on the dendrogram. The resulting cluster assignments are stored in the Seurat object.

Usage

CNVcluster(
  seuratObj,
  referenceVar = NULL,
  tumorLabel = NULL,
  k = NULL,
  h = NULL,
  plotDendrogram = F,
  plotClustersOnDendrogram = F,
  plotElbowPlot = F
)

Arguments

seuratObj

A Seurat object containing a "genomicScores" assay with a matrix of genomic scores for clustering.

referenceVar

The name of the metadata column in the Seurat object containing reference annotations.

tumorLabel

The label within referenceVar that specifies the tumor/malignant population (can be any type of annotation).

k

Optional. The number of clusters to cut the dendrogram into. If NULL, the optimal number of clusters is determined automatically using the elbow method.

h

Optional. The height at which to cut the dendrogram for clustering. If both k and h are provided, k takes precedence.

plotDendrogram

Logical. If TRUE, plots the dendrogram. Defaults to FALSE.

plotClustersOnDendrogram

Logical. If TRUE, highlights the clusters on the dendrogram. Defaults to FALSE.

plotElbowPlot

Logical. If TRUE, plots the elbow plot used for determining the optimal number of clusters. Defaults to FALSE.

Value

A Seurat object with an additional metadata column, cnv_clusters, containing the cluster assignments.

Details

The function computes a Manhattan distance matrix and performs hierarchical clustering using the Ward.D2 method. If k is not provided, the elbow method is applied to determine the optimal number of clusters based on the within-cluster sum of squares (WSS).

The clusters are assigned to the Seurat object under the metadata column cnv_clusters.