Creating visually appealing and informative heatmaps is a common task in data visualization. In R Programming Language the heatmap.2 function from the gplots package is a popular tool for generating heatmaps with enhanced features. However, one common issue users encounter is the need to adjust the margins of the plot to ensure that axis labels, titles, and other plot elements are fully visible. This article will guide you through the process of adding more margin to a heatmap.2 plot when using the png device for saving your plots.

What is heatmap.2 Plot?

A heatmap.2 plot is an enhanced version of the standard heatmap provided in R, available through the gplots package. It offers additional functionality and customization options that make it a powerful tool for visualizing complex datasets. Here’s a comprehensive explanation of what a heatmap.2 plot is, its features, and its applications.

Key Features of heatmap.2

The heatmap.2 function from the gplots package extends the functionality of the base R heatmap function by adding several features that enhance the visualization and interpretation of data.

• Dendrograms: heatmap.2 can display dendrograms (tree diagrams) along the rows and columns, which helps in visualizing the hierarchical clustering of the data. This is useful for identifying groups or clusters within the data.
• Color Key and Legend: It includes a color key (legend) that explains the mapping between colors and data values, making it easier to interpret the heatmap.
• Row and Column Scaling: The function allows for scaling of rows and/or columns to standardize the data before plotting, which is useful when variables are on different scales.
• Annotations: heatmap.2 supports the addition of row and column annotations, which can be used to label or highlight specific data points or categories.
• Customizable Color Schemes: The function allows users to specify custom color palettes, enabling more control over the visual appearance of the heatmap.

Now we will discuss Step-by-Step Guide to Add More Margin to a heatmap.2 Plot with the png Device.

Step 1: Install and Load Necessary Packages

First, ensure that you have the required packages installed. If not, you can install them using install.packages().

# Install the required packages
install.packages("gplots")
install.packages("RColorBrewer")

# Load the packages
library(gplots)
library(RColorBrewer)

Step 2: Create Sample Data

For demonstration purposes, we will create a sample dataset.

# Create a sample dataset
set.seed(123)
data_matrix <- matrix(rnorm(100), nrow = 10, ncol = 10)
rownames(data_matrix) <- paste("Gene", 1:10, sep = "_")
colnames(data_matrix) <- paste("Sample", 1:10, sep = "_")

Step 3: Set Up the PNG Device

When using the png device to save your plot, you can specify the dimensions and resolution. The key to adding more margin is to use the par() function to adjust the mar parameter, which controls the margin size.

# Set up the PNG device
png(filename = "heatmap.jpeg", width = 800, height = 800, res = 150)

# Adjust the margins using par()
par(mar = c(10, 10, 10, 10))

Step 4: Generate the Heatmap

Now, create the heatmap using heatmap.2 with the adjusted margins.

# Generate the heatmap
heatmap.2(
  data_matrix,
  main = "Sample Heatmap with Adjusted Margins",
  trace = "none",
  col = bluered(100),
  margins = c(10, 10)  # Adjusting the heatmap margins
)

Output:

Add More Margin to a heatmap.2 Plot with the png Device

From here we can get our saved image in jpeg format and after click on this we get our heatmap.

Add More Margin to a heatmap.2 Plot with the png Device

The heatmap.2() function creates a heatmap with enhanced features. The margins parameter inside heatmap.2 controls the size of the margins around the heatmap itself (excluding the space allocated by par(mar = c(...))).

Step 5. Close the PNG Device

After plotting, always remember to close the graphics device.

# Close the PNG device
dev.off()

The dev.off() function closes the current graphics device, finalizing the output file. It is essential to call this function to ensure that your plot is saved correctly.

Conclusion

By following the steps outlined in this article, you can effectively add more margin to a heatmap.2 plot when using the png device in R. Adjusting margins ensures that all plot elements are clearly visible, leading to more professional and informative visualizations. With these techniques, you can create heatmaps that not only convey your data effectively but also look polished and well-designed.