tme_cluster: Identification of TME Cluster

In IOBR: Immune Oncology Biological Research

Identification of TME Cluster

Description

Performs TME (Tumor Microenvironment) clustering analysis using various clustering methods. Supports feature selection, scaling, and automatic determination of optimal cluster number.

Usage

tme_cluster(
  input,
  features = NULL,
  pattern = NULL,
  id = NULL,
  scale = TRUE,
  method = "kmeans",
  min_nc = 2,
  max.nc = 6
)

Arguments

input	Data frame containing the input dataset.
features	Vector of features to use for clustering. Default is NULL (uses all columns or pattern-selected columns).
pattern	Regular expression pattern for selecting features. Default is NULL.
id	Column name for identifiers. Default is NULL (uses row names).
scale	Logical indicating whether to scale features. Default is TRUE.
method	Clustering method. Default is "kmeans".
min_nc	Minimum number of clusters to evaluate. Default is 2.
max.nc	Maximum number of clusters to evaluate. Default is 6.

Value

Data frame with cluster assignments appended.

Author(s)

Dongqiang Zeng

Examples

set.seed(123)
input_data <- data.frame(
  ID = paste0("Sample", 1:20),
  xCell_Tcells = rnorm(20),
  xCell_Bcells = rnorm(20),
  xCell_Macrophages = rnorm(20),
  Other_feature = rnorm(20)
)
result <- tme_cluster(
  input = input_data,
  pattern = "xCell",
  id = "ID",
  method = "kmeans"
)
table(result$cluster)

IOBR documentation built on May 30, 2026, 5:07 p.m.