Can I use absolut numbers (not log values) to make a Heatmap?

Question

[silas008]

Hi, guys

I have a RNA-seq data with 3 different groups treated with different diets. I already made the heatmap with the log2 values from the comparison between the groups.

Now I want to make another heatmap containig not the comparison between the groups but the normalized expression values (in this case I will have a heatmap of my 3 groups).

I have the data from DESeq2 but I don't know if I can use it directly in the heatmap or I need to do some additional normalization before that.

Thank you very much

Answer 1

[Kevin Blighe]

The usual approach is to plot the normalised values, not log (base 2) fold-changes. One first identifies statistically significant genes an then subsets their normalised expression matrix such that it only includes the statistically significant genes. From this subset, hierarchical clustering can be performed (with a heatmap being generated, in addition) for the purposes of determining how well your selection of statistically significant genes can actually segregate your conditions that were compared during differential expression.

I and others have posted a lot of answers with code showing how you can generate a dendrogram with heatmap from any matrix of values:

gplots

• A: Heatmap based with FPKM values
• A: Hierarchical Clustering in single-channel agilent microarray experiment

ComplexHeatmap

• A: Complex Heatmap: Changing order of clusters
• C: Hierarchical Clustering in single-channel agilent microarray experiment
• C: how to cluster genes in heatmap
• A: How to plot a heatmap with two different distance matrices for X and Y

pheatmap:

• A: extract dendrogram cluster from pheatmap

Other:

• A: how to draw circular dendrogram with distance information

Kevin

[silas008]

Thank you very much, Kevin!!!

[silas008]

Hi, Kevin.

I have another question, I will appreciate if you can help me.

In my data, actually, I don't have control group.

Image that you want to measure the expression of a set of genes in tree different dog breeds. In many cases you will no have a control group, you are just comparing them.

My question is if the normalized data from DEseq2, plotted in a heatmap, will represent well the differences between the absolute expression values of these genes. Because what people normally do is to compare the control group with other treated groups and then they get the log2 of theses comparisons to make a heatmap.

What is the best way to represent what I want to show in this case.

Thank you very much again.

[Kevin Blighe]

No, what people normally do is conduct a differential expression analysis, identify the statistically significantly differentially expressed genes, and then filter their normalised expression data matrix to only include these statistically significantly differentially expressed genes. This filtered data matrix is then plotted via dendrogram / heatmap to see if the genes can segregate both groups through clustering.

Answer 2

[h.mon]

I have the data from DESeq2 but I don't know if I can use it directly in the heatmap or I need to do some additional normalization before that.

You can, in the sense it will produce a heatmap, but it won't be useful. You certainly need to perform further normalization (but some heatmap functions have normalization built-in) for the heatmap produce meaningful visualization. I would suggest you follow one of the outstanding tutorial out there, from DESeq2 vignette to Ming Tang's Heatmap demystified, not to mention some of Kevin Blighe's posts on the subject.

[silas008]

Thank you very much!!!