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.
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"
)
#> ℹ Best number of TME clusters: 3
#> ℹ Cluster distribution:
#> 1 2 3
#> 10 8 2
table(result$cluster)
#>
#> TME1 TME2 TME3
#> 10 8 2