set.seed(123)
genes <- paste0("Gene", 1:20)
tissues <- paste0("Tissue", 1:5)
expression_data <- matrix(rnorm(100), nrow = 20, ncol = 5, dimnames = list(genes, tissues))
# Perform K-means clustering
k <- 3 # Number of clusters
kmeans_result <- kmeans(expression_data, centers = k)
# Add cluster assignments to the original data frame and keep it as a data frame
expression_data_with_clusters <- data.frame(expression_data, Cluster = as.factor(kmeans_result$cluster))
# Visualize the clustered data using pheatmap
pheatmap(
expression_data,
cluster_cols = FALSE,
annotation_row = expression_data_with_clusters[rownames(expression_data), "Cluster", drop = FALSE],
main = "K-means Clustering Heatmap",
fontsize_col = 8
)
plot Kmeans heatmap for genes
最新推荐文章于 2025-05-17 21:02:57 发布