How do you find the pattern in a heatmap without clustering?
Now we have a heatmap showing the data as it is, without any row or column clustering. Even without clustering, We can see that there is a pattern in the data, some columns are more similar to each other than the others. We can cluster the data by columns using “cluster_cols = TRUE” and see the pattern easily.
What is the pheatmap package?
The pheatmap package, created by Raivo Kolde, offers extensive control over dimensions and appearance of heatmaps. A big advantage of the package is that it enables the user to visually cluster heatmaps. Before we dive deeper into the exemplifying R codes… Here you can find the documentation of the pheatmap package.
How do I use the pheatmap function?
The pheatmap function is similar to the default base R heatmap, but provides more control over the resulting plot. You can pass a numeric matrix containing the values to be plotted. If the values of the matrix are not normalized you can normalize them by rows ( "row") or by columns ( "column") making use of the scale argument.
What does the default pheatmap look like?
We get a heatmap that looks like this. By default pheatmap does a few things. For example, it uses diverging color palette to differentiate the values by different colors. And also pheatmap clusters columns and rows by default. It also shows the tree/dendrogram of the cluster with the heatmap. We also get a legend mapping colors to data values.
What is annotation function in pheatmap?
Specifically, you can input an independent data frame with annotations to the rows or columns of the heatmap matrix.
Does pheatmap take a matrix?
First, pheatmap only takes the numeric matrix object as input. So, we need to transfer the numeric part of the data frame to a matrix by removing the first 5 columns of categorical data.
The pheatmap function
The pheatmap function is similar to the default base R heatmap, but provides more control over the resulting plot. You can pass a numeric matrix containing the values to be plotted.
Clustering
You can pass a hclust object to the cluster_rows argument or set it to FALSE to remove the rows dendrogram.
Color customization
The border_color controls the border of the cells. The default value is "grey60".
Legend customization
The breaks of the legend can be customized with legend_breaks, passing the desired values as a vector.
