Extracting Row Names from Your Heatmap Using R's ComplexHeatmap Library

Описание: Learn how to effortlessly extract row names from your heatmaps created with R's ComplexHeatmap library, retaining the order they appear in the visualization.
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This video is based on the question https://stackoverflow.com/q/76513412/ asked by the user 'Angelo' ( https://stackoverflow.com/u/735764/ ) and on the answer https://stackoverflow.com/a/76513955/ provided by the user 'margusl' ( https://stackoverflow.com/u/646761/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Extracting Row Names from Your Heatmap Using R's ComplexHeatmap Library

Heatmaps are a powerful visualization tool in R, especially useful in the realms of bioinformatics and data science. If you've created a heatmap using the ComplexHeatmap library in R, you may want to extract the row names in the order they appear on the heatmap. This post will guide you in achieving just that, step by step.

Understanding the Context

When you generate a heatmap, the rows and columns can be clustered based on the data. After performing this clustering, it can be challenging to determine the exact order of the row names. Extracting these row names while maintaining their visual order can enhance your data analysis and make your reporting clearer.

In this example, we will use the sample gene expression data provided and the code that generates a heatmap. This blog will also show you how to effectively extract the desired row names.

Sample Data

Let's start with the sample data that you'll be using to create a heatmap:

[[See Video to Reveal this Text or Code Snippet]]

This data consists of gene expression levels across different conditions. You can load this data into R using the following code:

[[See Video to Reveal this Text or Code Snippet]]

Creating a Heatmap

Once you have your data ready, you can utilize the ComplexHeatmap library to create a heatmap. Here’s how to do that:

[[See Video to Reveal this Text or Code Snippet]]

Explanation of the Code

Scaling the Data: t(apply(mat, 1, scale)) scales the rows of your matrix, which is a common practice before visualizing data to ensure better interpretability.

Creating the Heatmap: The Heatmap() function creates the heatmap with clustered rows and columns.

Extracting Row Names

Now that your heatmap is created, you can extract the row names in the order they appear using the following code snippet:

[[See Video to Reveal this Text or Code Snippet]]

What This Code Does

Drawing the Heatmap: Calling draw(ht) displays the heatmap.

Extracting Row Names: row_order(ht) retrieves the order of the rows as displayed in the heatmap, allowing you to access the original row names using rownames(mat.z).

Conclusion

By following these steps, you can create impressive heatmaps and extract the ordered row names for further analysis. This approach provides clarity for your reports and research findings. Feel free to copy and adapt the provided code snippets to your own datasets, and happy coding!

If you have any questions or further topics you'd like explored in R, let me know in the comments!