<p>As others already pointed out, there is no official heatmap color scheme. I am not sure there is an official color scheme for any other types of plots either.</p>
<p>However, heatmaps seem to be far more standardized. Traditionally, heatmaps have been red-black-green as you originally stated. Most heatmaps from the microarray era and early RNA-seq are like that. You can have a heatmap for any type of data, but the majority is for gene expression. A lot of tools and tutorials were written back then, so they have that color scheme. From about 2008 to 2012, most people switched to the red-white-blue (or red-yellow-blue) color scheme. Switching green to blue avoids the color-blindness issue. Switching black to white is better for the ink if you print your papers and generally looks better on white background.</p>
<p>I originally found red as high to be confusing because I was thinking in financial terms (if the market is red, it's down). Now I think of it as a water faucet (red is hot, blue is cold).</p>
<p>Edit: In the last year or so, the <a href="https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html" rel="nofollow noreferrer">viridis</a> palette started to become widely used. It's far from the standard, but could become more popular in the future.</p>

CC BY-SA 4.0
2020-07-03T21:29:00.030Z
I really like this analogy, the Red is hot, Blue is cold will probably help me a lot! I agree that the "financial" use of red and green is probably the source of my switched intuition.
Dan
CC BY-SA 4.0
2020-07-03T14:59:04.420Z
2020-07-05T16:27:00.753Z
2020-07-05T16:27:00.753Z
burger
<p>Although there is no standard as DeepTools' Devon Ryan said, there are still some habits. Usually red means upregulated, as you can see in the default color scheme in MATLAB's clustergram function. But you also want to make sure color-blinded people can see the difference. So another color scheme might be better, such as red=high while blue=low.
Anyway, if you can easily flip the color, using red to represent high is expected.</p>

CC BY-SA 4.0
2020-06-20T21:35:49.350Z
2020-06-20T21:35:49.350Z
Code42
<p>In the absence of any yet-identified official recommendations, I will update this answer with resources as I find them:</p>
<p><strong>Example usage in tutorials:</strong></p>
<ul>
<li><a href="https://www.ebi.ac.uk/training/online/course/functional-genomics-ii-common-technologies-and-data-analysis-methods/biological-0" rel="nofollow noreferrer">EMBL Training: Red=Up, Black=NC, Green=Down</a></li>
</ul>
<p><strong>Program Defaults:</strong></p>
<ul>
<li><a href="https://docs.patricbrc.org/user_guides/organisms_taxon/transcriptomics_gene_heatmap.html#:%7E:text=The%20default%20color%20scheme%20is,off%20setting%20are%20colored%20black." rel="nofollow noreferrer">PATRIC Webiste: Red=Up, Black=NC, Green=Down</a></li>
</ul>
<p><strong>Guides:</strong></p>
<ul>
<li><a href="https://blog.bioturing.com/2018/09/24/heatmap-color-scale/" rel="nofollow noreferrer">Bio Turing Blog: Dos and don’ts for a heatmap color scale</a></li>
<li><a href="https://sebastianraschka.com/Articles/heatmaps_in_r.html#optional-choosing-custom-color-palettes-and-color-breaks" rel="nofollow noreferrer">sebastianraschka: A short tutorial for decent heat maps in R</a></li>
</ul>
<p><strong>Tools (by year):</strong></p>
<ul>
<li>(-2020) Web, R, CLI: <a href="https://software.broadinstitute.org/morpheus/" rel="nofollow noreferrer">MORPHEUS: Versatile matrix visualization and analysis software</a></li>
<li>(2019) Web, R, CLI: <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0204542" rel="nofollow noreferrer">NOJAH: NOt Just Another Heatmap for genome-wide cluster analysis</a></li>
<li>(2017) Web, Jupyter: <a href="https://www.nature.com/articles/sdata2017151" rel="nofollow noreferrer">Clustergrammer, a web-based heatmap visualization and analysis tool for high-dimensional biological data</a></li>
<li>(2017) Web, R: <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0176334" rel="nofollow noreferrer">shinyheatmap: Ultra fast low memory heatmap web interface for big data genomics</a></li>
<li>(2016) R: <a href="https://academic.oup.com/bioinformatics/article/32/18/2847/1743594" rel="nofollow noreferrer">Complex heatmaps reveal patterns and correlations in multidimensional genomic data</a></li>
<li>(2016) Web: <a href="https://pubmed.ncbi.nlm.nih.gov/27190236/" rel="nofollow noreferrer">Heatmapper: Web-Enabled Heat Mapping for All</a></li>
<li>(&lt;2016) GUI, Java, R: <a href="https://software.broadinstitute.org/GENE-E/index.html" rel="nofollow noreferrer">GENE-E</a></li>
<li>(2015) R: <a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-15-S10-P16" rel="nofollow noreferrer">Heatmap3: an improved heatmap package with more powerful and convenient features</a></li>
<li>(2011) GUI, CLI: <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0019541" rel="nofollow noreferrer">Gitools: Analysis and Visualisation of Genomic Data Using Interactive Heat-Maps</a></li>
</ul>

CC BY-SA 4.0
2020-06-29T12:59:22.327Z
2020-07-02T13:30:33.677Z
2020-07-02T13:30:33.677Z
Dan
<p>I have recently found myself making multiple heatmaps for visualization of differential gene expression results between replicates in two experimental conditions.</p>
<p>The default settings in the plotting software I use color:</p>
<ul>
<li>Upregulated genes --&gt; red</li>
<li>Downregulated genes --&gt; green</li>
<li>Unchanged genes --&gt; black</li>
</ul>
<p>My intuition <em>screams</em> at me that this color scheme is reversed, and that upregulated genes should be green and that downregulated genes should be red. I have asked several labmates about their intuition regarding this color scheme, and have found about a 50/50 split in those that intuitively agree with each different scheme.</p>
<p>In my searching on this topic, I have found that <a href="https://docs.patricbrc.org/user_guides/organisms_taxon/transcriptomics_gene_heatmap.html#:%7E:text=The%20default%20color%20scheme%20is,off%20setting%20are%20colored%20black." rel="nofollow noreferrer">several programs</a> plot heatmaps with the same default colors as the program I'm using (red=upregulated, green=downregulated). Additionally, I have been told in conversation that this is essentially an accepted standard.</p>
<p>If this is indeed the convention, I will begin trying to rewire my intuition, but I want to confirm that it is before I do so. However I have not yet been able to find any &quot;official&quot; guidelines from agencies, publishers, authorities in the field, etc., specifying the use of red/green in heatmaps.</p>
<p>I do know that there are many <a href="https://blog.bioturing.com/2018/09/24/heatmap-color-scale/" rel="nofollow noreferrer">suggestions for alternative heatmap color schemes</a>, but I'm interested in finding an official answer for the red/green scheme specifically.</p>
<p><strong>Edit:</strong> Several comments have stated that there is no such standard as described above. Therefore I am modifying the following question somewhat to:</p>
<p><strong>Are there &quot;official&quot; guidelines from agencies, publishers, authorities in the field, etc., specifying the use of red/green in heatmaps?
Or conversely are there any “official” guidelines stating that there is no such specification and/or that any such selection of colors is acceptable?</strong></p>

CC BY-SA 4.0
2020-06-19T13:01:07.913Z
No, there are no official guidelines.
Devon Ryan
CC BY-SA 4.0
2020-06-19T13:02:18.753Z
If it is an accepted standard, that seems hard to believe.
Dan
CC BY-SA 4.0
2020-06-19T13:03:17.863Z
There is no accepted standard on this and the somewhat common red/green coloring is absolutely terrible (and backwards).
Devon Ryan
CC BY-SA 4.0
2020-06-19T14:37:12.550Z
Red/green is generally not a great colour scheme since it is a common colour blindness
Chris_Rands
CC BY-SA 4.0
2020-06-19T15:48:13.700Z
Personally, I try to avoid heatmaps as much as I can. Usually, I find them confusing and I find it hard to mentally convert colour intensities to quantities, no matter what the colour scheme is. Having said that, I spent the whole of today dealing with heatmap.2. BTW, if you pin me down I'm on the side of upregulated=red (don't ask me why). Sorry, not a helpful comment...
dariober
<differential-expression><visualization><heatmap>
Is there an "official" standard usage of Red and Green on differential gene expression heatmaps?
# Is there an "official" standard usage of Red and Green on differential gene expression heatmaps?

(Asked by: username_0 on 2020-06-19)

I have recently found myself making multiple heatmaps for visualization of differential gene expression results between replicates in two experimental conditions.

The default settings in the plotting software I use color:

* Upregulated genes --> red
* Downregulated genes --> green
* Unchanged genes --> black

My intuition *screams* at me that this color scheme is reversed, and that upregulated genes should be green and that downregulated genes should be red. I have asked several labmates about their intuition regarding this color scheme, and have found about a 50/50 split in those that intuitively agree with each different scheme.

In my searching on this topic, I have found that [several programs](https://docs.patricbrc.org/user_guides/organisms_taxon/transcriptomics_gene_heatmap.html#:%7E:text=The%20default%20color%20scheme%20is,off%20setting%20are%20colored%20black.) plot heatmaps with the same default colors as the program I'm using (red=upregulated, green=downregulated). Additionally, I have been told in conversation that this is essentially an accepted standard.

If this is indeed the convention, I will begin trying to rewire my intuition, but I want to confirm that it is before I do so. However I have not yet been able to find any "official" guidelines from agencies, publishers, authorities in the field, etc., specifying the use of red/green in heatmaps.

I do know that there are many [suggestions for alternative heatmap color schemes](https://blog.bioturing.com/2018/09/24/heatmap-color-scale/), but I'm interested in finding an official answer for the red/green scheme specifically.

**Edit:** Several comments have stated that there is no such standard as described above. Therefore I am modifying the following question somewhat to:

**Are there "official" guidelines from agencies, publishers, authorities in the field, etc., specifying the use of red/green in heatmaps?
Or conversely are there any “official” guidelines stating that there is no such specification and/or that any such selection of colors is acceptable?**

**Tags:** differential-expression, visualization, heatmap
> **Comments:**
> **username_1**: No, there are no official guidelines.  
> **username_0**: If it is an accepted standard, that seems hard to believe.  
> **username_1**: There is no accepted standard on this and the somewhat common red/green coloring is absolutely terrible (and backwards).  
> **username_2**: Red/green is generally not a great colour scheme since it is a common colour blindness  
> **username_3**: Personally, I try to avoid heatmaps as much as I can. Usually, I find them confusing and I find it hard to mentally convert colour intensities to quantities, no matter what the colour scheme is. Having said that, I spent the whole of today dealing with heatmap.2. BTW, if you pin me down I'm on the side of upregulated=red (don't ask me why). Sorry, not a helpful comment...  

---

## 3 answers

### Answer by username_4 on 2020-07-03. Score: 3

As others already pointed out, there is no official heatmap color scheme. I am not sure there is an official color scheme for any other types of plots either.

However, heatmaps seem to be far more standardized. Traditionally, heatmaps have been red-black-green as you originally stated. Most heatmaps from the microarray era and early RNA-seq are like that. You can have a heatmap for any type of data, but the majority is for gene expression. A lot of tools and tutorials were written back then, so they have that color scheme. From about 2008 to 2012, most people switched to the red-white-blue (or red-yellow-blue) color scheme. Switching green to blue avoids the color-blindness issue. Switching black to white is better for the ink if you print your papers and generally looks better on white background.

I originally found red as high to be confusing because I was thinking in financial terms (if the market is red, it's down). Now I think of it as a water faucet (red is hot, blue is cold).

Edit: In the last year or so, the [viridis](https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html) palette started to become widely used. It's far from the standard, but could become more popular in the future.

> **Comments:**
> **username_0**: I really like this analogy, the Red is hot, Blue is cold will probably help me a lot! I agree that the "financial" use of red and green is probably the source of my switched intuition.  

---

### Answer by username_5 on 2020-06-20. Score: 1

Although there is no standard as DeepTools' Devon Ryan said, there are still some habits. Usually red means upregulated, as you can see in the default color scheme in MATLAB's clustergram function. But you also want to make sure color-blinded people can see the difference. So another color scheme might be better, such as red=high while blue=low.
Anyway, if you can easily flip the color, using red to represent high is expected.


---

### Answer by username_0 on 2020-06-29. Score: 0

In the absence of any yet-identified official recommendations, I will update this answer with resources as I find them:

**Example usage in tutorials:**

* [EMBL Training: Red=Up, Black=NC, Green=Down](https://www.ebi.ac.uk/training/online/course/functional-genomics-ii-common-technologies-and-data-analysis-methods/biological-0)

**Program Defaults:**

* [PATRIC Webiste: Red=Up, Black=NC, Green=Down](https://docs.patricbrc.org/user_guides/organisms_taxon/transcriptomics_gene_heatmap.html#:%7E:text=The%20default%20color%20scheme%20is,off%20setting%20are%20colored%20black.)

**Guides:**

* [Bio Turing Blog: Dos and don’ts for a heatmap color scale](https://blog.bioturing.com/2018/09/24/heatmap-color-scale/)
* [sebastianraschka: A short tutorial for decent heat maps in R](https://sebastianraschka.com/Articles/heatmaps_in_r.html#optional-choosing-custom-color-palettes-and-color-breaks)

**Tools (by year):**

* (-2020) Web, R, CLI: [MORPHEUS: Versatile matrix visualization and analysis software](https://software.broadinstitute.org/morpheus/)
* (2019) Web, R, CLI: [NOJAH: NOt Just Another Heatmap for genome-wide cluster analysis](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0204542)
* (2017) Web, Jupyter: [Clustergrammer, a web-based heatmap visualization and analysis tool for high-dimensional biological data](https://www.nature.com/articles/sdata2017151)
* (2017) Web, R: [shinyheatmap: Ultra fast low memory heatmap web interface for big data genomics](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0176334)
* (2016) R: [Complex heatmaps reveal patterns and correlations in multidimensional genomic data](https://academic.oup.com/bioinformatics/article/32/18/2847/1743594)
* (2016) Web: [Heatmapper: Web-Enabled Heat Mapping for All](https://pubmed.ncbi.nlm.nih.gov/27190236/)
* (<2016) GUI, Java, R: [GENE-E](https://software.broadinstitute.org/GENE-E/index.html)
* (2015) R: [Heatmap3: an improved heatmap package with more powerful and convenient features](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-15-S10-P16)
* (2011) GUI, CLI: [Gitools: Analysis and Visualisation of Genomic Data Using Interactive Heat-Maps](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0019541)


---

