text: user3968: I want to use the DotPlot function from Seurat v3 to visualise the expression of some genes across clusters. However when the expression of a gene is zero or very low, the dot size is so small that it is not clearly visible when printed on paper. Please is there a possibility to increase the minimum dot size in the DotPlot function to make the dot sizes more visible when printed?
  For example, I would like to have a minimum dot size set to be like 
  
  from this publication
  Rather than:
  
  from this other publication
  Thank you in advance for your helpful hint.
  
  user3773: Did you try to use DotPlot(..., scale.by = "size")?
  In contrast to the default scale.by= "radius", this will link the area (==2*pi*r^2), not the radius, of the circles to the fraction of cells expressing the feature.
  This corresponds much better to our perception of size and will make differences in low values easier to see.
  Reading ?Seurat::DotPlot the scale.min parameter looked promising but looking at the code it seems to censor the data as well.
  Since Seurat's plotting functionality is based on ggplot2 you can also adjust the color scale by simply adding scale_fill_viridis() etc. to the returned plot. This might also work for size. Try something like:
  DotPlot(...) + scale_size(range = c(5, 10)) # will likely warn about supplying the same scale twice
  
  Apart from this, Seurat's plotting system is not very hackable and I find it much easier to extract the relevant data and plot them myself with ggplot2.
  Yet another comment: Your plot with the strong differences looks much more convincing to me wrt. to the marker property of these genes than the cited plot.
  
original_text: 3968: <p>I want to use the DotPlot function from Seurat v3 to visualise the expression of some genes across clusters. However when the expression of a gene is zero or very low, the dot size is so small that it is not clearly visible when printed on paper. Please is there a possibility to increase the minimum dot size in the DotPlot function to make the dot sizes more visible when printed?</p>
  
  <p>For example, I would like to have a minimum dot size set to be like </p>
  
  <p><a href="https://i.stack.imgur.com/aQfL6.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/aQfL6.png" alt="in this image"></a></p>
  
  <p>from <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5746044/figure/F11/" rel="nofollow noreferrer">this publication</a></p>
  
  <p>Rather than:</p>
  
  <p><a href="https://i.stack.imgur.com/KqEwE.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/KqEwE.png" alt="this image"></a></p>
  
  <p>from <a href="https://www.nature.com/articles/s41598-018-24725-0/figures/1#" rel="nofollow noreferrer">this other publication</a></p>
  
  <p>Thank you in advance for your helpful hint.</p>
   3773: <p>Did you try to use <code>DotPlot(..., scale.by = &quot;size&quot;)</code>?</p>
  <p>In contrast to the default <code>scale.by= &quot;radius&quot;</code>, this will link the <em>area</em> (<code>==2*pi*r^2</code>), not the radius, of the circles to the fraction of cells expressing the feature.
  This corresponds much better to our perception of size and will make differences in low values easier to see.</p>
  <p>Reading <code>?Seurat::DotPlot</code> the <code>scale.min</code> parameter looked promising but looking at <a href="https://github.com/satijalab/seurat/blob/c9f2660ee6b88189acc3ff4aa6088a46a2558dd3/R/visualization.R#L1980" rel="nofollow noreferrer">the code</a> it seems to censor the data as well.</p>
  <p>Since Seurat's plotting functionality is based on <code>ggplot2</code> you can also adjust the color scale by simply adding <code>scale_fill_viridis()</code> etc. to the returned plot. This might also work for <code>size</code>. Try something like:</p>
  <pre class="lang-r prettyprint-override"><code>DotPlot(...) + scale_size(range = c(5, 10)) # will likely warn about supplying the same scale twice
  </code></pre>
  <p>Apart from this, Seurat's plotting system is not very hackable and I find it much easier to extract the relevant data and plot them myself with <code>ggplot2</code>.</p>
  <p>Yet another comment: Your plot with the strong differences looks much more convincing to me wrt. to the marker property of these genes than the cited plot.</p>
  