draw.2D.text: Visualize Sample Clustering Result in 2D Plot with Sample...

View source: R/pipeline_functions.R

draw.2D.textR Documentation

Visualize Sample Clustering Result in 2D Plot with Sample Names

Description

draw.2D.text creates a 2D plot with sample names labeled, to visualize the sample clustering result.

Usage

draw.2D.text(
  X,
  Y,
  class_label,
  class_text = NULL,
  xlab = "PC1",
  ylab = "PC2",
  legend_cex = 0.8,
  main = "",
  point_cex = 1,
  text_cex = NULL,
  use_color = NULL,
  pre_define = NULL
)

Arguments

X

a vector of numerics, the x coordinates of points in the plot. If user would like to create a PCA biplot, this parameter should be the first component.

Y

a vector of numerics, the y coordinates of points in the plot. If user would like to create a PCA biplot, this parameter should be the second component.

class_label

a vector of characters, labels or categories of samples. The vector name should be sample names.

class_text

a vector of characters, the user-defined sample names to label each data points in the plot. If NULL, will use the names of class_label. Default is NULL.

xlab

character, the label for x-axis. Default is "PC1".

ylab

character, the label for y-axis. Default is "PC2".

legend_cex

numeric, giving the amount by which the text of legend should be magnified relative to the default. Default is 0.8.

main

character, an overall title for the plot. Default is "".

point_cex

numeric, giving the amount by which the size of the data points should be magnified relative to the default. Default is 1.

text_cex

numeric, giving the amount by which the text of class_text should be magnified relative to the default. Default is NULL.

use_color

a vector of color codes, colors to be assigned to each member of display label. Default is brewer.pal(9, 'Set1').

pre_define

a vector of characters, pre-defined color codes for a certain input (e.g. c("blue", "red") with names c("A", "B")). Default is NULL.

Value

Return a logical value. If TRUE, the plot has been created successfully.

Examples

mat1 <- matrix(rnorm(2000,mean=0,sd=1),nrow=100,ncol=20)
rownames(mat1) <- paste0('Gene',1:nrow(mat1))
colnames(mat1) <- paste0('Sample',1:ncol(mat1))
pc <- stats::prcomp(t(mat1))$x
pred_label <- kmeans(pc,centers=4)$cluster ## this can use other cluster results
draw.2D.text(X=pc[,1],Y=pc[,2],class_label=pred_label,
             point_cex=5,text_cex=0.5)

jyyulab/NetBID documentation built on Dec. 23, 2024, 6:34 a.m.