cytof_heatmap: Heatmap plot of cluster mean value results

In JinmiaoChenLab/cytofkit2: cytofkit2: an integrated mass cytometry data analysis pipeline. Cytofkit provides functions for data pre-processing, fast clustering, data visualization through linear or non-linear dimensionality reduction, automatic identification of cell subsets, and inference of the relatedness between cell subsets

Heatmap plot of cluster mean value results

Description

Heatmap plot of cluster mean value results

Usage

cytof_heatmap(
  data,
  baseName = "Cluster",
  scaleMethod = "none",
  dendrogram = c("both", "row", "column", "none"),
  colPalette = c("bluered", "greenred", "spectral1", "spectral2"),
  cex_row_label = NULL,
  cex_col_label = NULL,
  key.par = list(mgp = c(1.5, 0.5, 0), mar = c(3, 2.5, 3.5, 1)),
  keysize = 1.4,
  margins = c(5, 5)
)

Arguments

data	A matrix with rownames and colnames
baseName	The name as a prefix in the title of the heatmap.
scaleMethod	Method indicating if the values should be centered and scaled in either the row direction or the column direction, or none. The default is 'none'.
dendrogram	Control the dengrogram on row or column, selection includes 'both', 'row', 'column', 'none'.
colPalette	Use selected colour palette, includes 'bluered', 'greenred', 'spectral1' and 'spectral2'.
cex_row_label	Text size for row labels.
cex_col_label	Text size for column labels.
key.par	Graphical parameters for the color key.
keysize	Numeric value indicating the size of the key.
margins	Numeric vector of length 2 containing the margins (see par(mar= *)) for column and row names, respectively.

Value

A heatmap object from gplots

Examples

m1 <- c(rnorm(300, 10, 2), rnorm(400, 4, 2), rnorm(300, 7))
m2 <- c(rnorm(300, 4), rnorm(400, 16), rnorm(300, 10, 3))
m3 <- c(rnorm(300, 16), rnorm(400, 40, 3), rnorm(300, 10))
m4 <- c(rnorm(300, 7, 3), rnorm(400, 30, 2), rnorm(300, 10))
m5 <- c(rnorm(300, 27), rnorm(400, 40, 1),rnorm(300, 10))
c <- c(rep(1,300), rep(2,400), rep(3,300))
rnames <- paste(paste('sample_', c('A','B','C','D'), sep = ''), 
rep(1:250,each = 4), sep='_') 
exprs_cluster <- data.frame(cluster = c, m1 = m1, m2 = m2, m3 = m3, m4 = m4, m5 = m5)
row.names(exprs_cluster) <- sample(rnames, 1000)
cluster_mean <- aggregate(. ~ cluster, data = exprs_cluster, mean)
rownames(cluster_mean) <- paste("cluster_", cluster_mean$cluster, sep = "")
p = cytof_heatmap(cluster_mean[, -which(colnames(cluster_mean) == "cluster")])

JinmiaoChenLab/cytofkit2 documentation built on May 12, 2022, 8:09 a.m.