text: user4595: I returned a FeaturePlot from Seurat to ggplot. My plot has a weird range of colours as below
  
  I produced this plot by this code
  > head(mat[1:4,1:4])
               s1.1        s1.2 s1.3       s1.4
  DDB_G0267178    0 0.009263254    0 0.01286397
  DDB_G0267180    0 0.000000000    0 0.00000000
  DDB_G0267182    0 0.000000000    0 0.03810585
  DDB_G0267184    0 0.000000000    0 0.00000000
  > 
  
  I have converted expression matrix to a binary matrix by 2 as a threshold
  
  mat[mat < 2] <- 0
  mat[mat > 2] <- 1
  
  > head(exp[1:4,1:4])
               s1.1 s1.2 s1.3 s1.4
  DDB_G0267382    0    0    0    1
  DDB_G0267438    0    0    0    1
  DDB_G0267466    0    0    0    0
  DDB_G0267476    0    0    1    0
  > 
  > exp=colSums(exp)
  > exp=as.matrix(exp)
  > colnames(exp)="value"
  > exp=as.data.frame(exp)
  > cc <- AddMetaData(object = seurat, metadata = exp)
  > cc <- SetAllIdent(object = cc, id = "value")
  > TSNEPlot(object = cc, do.return= TRUE)
  
  How I can convert this range to a gradient of colours for example in 8-18, 18-28, 28-38, 38-48 range in blue to yellow please? Something like below
  
  Thank you for any help
  Then by ggplot now I scaled my colours but I don't like my clusters as so and I don't know how to retain my clusters as a featureplot by this new color gradient 
  > head(cc@meta.data)
       nGene    nUMI    orig.ident res.0.7 CELL STAGE GENO dataset stage.nice celltype value
  s1.1  4331  373762 SeuratProject       0 s1.1   H16   WT       1        H16        0    34
  s1.2  5603 1074639 SeuratProject       0 s1.2   H16   WT       1        H16        0    26
  s1.3  2064   49544 SeuratProject       0 s1.3   H16   WT       1        H16        0    27
  s1.4  4680  772399 SeuratProject       1 s1.4   H16   WT       1        H16        1    29
  s1.5  3876  272356 SeuratProject       1 s1.5   H16   WT       1        H16        1    21
  s1.6  2557  122314 SeuratProject       0 s1.6   H16   WT       1        H16        0    31
  
  > ggplot(as.data.frame(cc@meta.data), aes(x = cc@meta.data$CELL, y = cc@meta.data$res.0.7, colour =cc@meta.data$value)) + 
  +     geom_point(size = 5) +
  +     scale_colour_gradient(low = "yellow", high = "blue")
  
  
  By below code I obtained a tsne in link
  > cols <-  scales::seq_gradient_pal(low="beige", high="red", space="Lab")(seq(from=0, to=1,length.out=48))
  > 
  > TSNEPlot(cc, colors.use=cols)
  
  enter link description here
  Now I want to know how I could convert this range to a 8-18, 18-28, 28-38, 38-48 colour range as a gradient of blue to yellow?
  
  user181: TSNEPlot()
  TSNEPlot() will always treat your variables as discrete. My approach is to manually generate a gradient with unique colors for each factor level and pass it to the cols.use argument in TSNEPlot(). 
  #generate values for testing purposes, one value for each cell
  value <- sample(seq(from=8, to=48, by=1), size = length(rownames(unfiltered_cca@meta.data)), replace=TRUE)
  names(value) <- rownames(exp@meta.data)
  exp <- AddMetaData(object=exp, metadata=value, col.name="value")
  exp <-  SetIdent(exp, ident.use=exp@meta.data$value)
  #create a gradient between specified colors, multiply by sequence to get appropriate length
  #length.out is the number of different colors, number of factor levels
  cols <-  scales::seq_gradient_pal(low="beige", high="red", space="Lab")(seq(from=0, to=1,length.out=48))
  
  
  TSNEPlot(exp, colors.use=cols)
  
  
  I would present this with no legend:
  TSNEPlot(exp, colors.use=cols, no.legend = TRUE)
  
  
  FeaturePlot()
  You can also simply use FeaturePlot() instead of TSNEPlot() to visualize the gradient. Using the same data as above:
  FeaturePlot(object = exp, features.plot = "value", reduction.use = "tsne", no.legend = FALSE, cols.use = c("beige", "red"))
  
  
  You ask for a continuous scale, but this is not what is shown in your second plot.  You have a different color for each discrete range of values. I assume here that you want a continuous gradient. To achieve something like the second plot you provided requires a different approach.
  
  user181: If you would like to color discrete intervals on a gradient as opposed to having a continuous gradient (like your second plot), use this approach. 
  It is similar to the approach in the answer I posted with the continuous scale, but we simply break up the continuous scale in to intervals and color them by these intervals.
  #generate values for testing purposes, one value for each cell, add to object
  value <- sample(seq(from=8, to=46, by=1), size = length(rownames(exp@meta.data)), replace=TRUE)
  exp <- AddMetaData(object=exp, metadata=value, col.name="value")
  
  #encode the continuous values as factors, determined by the interval they fall in to
  value_breaks <- cut(exp@meta.data$value, breaks = c(8,18,28,38,46), include.lowest=TRUE, right=FALSE)
  
  #name the breaks by cell so they can be added by AddMetaData(), add them
  names(value_breaks) <- rownames(exp@meta.data)
  exp <- AddMetaData(object=exp, metadata=value_breaks, col.name="value_breaks")
  
  exp <-  SetIdent(exp, ident.use=exp@meta.data$value_breaks)
  
  #create a gradient between specified intervals
  #length.out is the number of different colors, number of factor levels
  cols <- scales::seq_gradient_pal(low="blue", high="yellow", space="Lab")(seq(from=0, to=1,length.out=4))
  
  TSNEPlot(exp, colors.use=cols)
  
  
  The label in the legend are classic mathematical notation for intervals. You can add your own labels if you wish in the cut() function.
  
original_text: 4595: <p>I returned a FeaturePlot from Seurat to ggplot. My plot has a weird range of colours as below</p>
  
  <p><a href="https://i.stack.imgur.com/FhN0Y.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/FhN0Y.png" alt="enter image description here"></a></p>
  
  <p>I produced this plot by this code</p>
  
  <pre><code>&gt; head(mat[1:4,1:4])
               s1.1        s1.2 s1.3       s1.4
  DDB_G0267178    0 0.009263254    0 0.01286397
  DDB_G0267180    0 0.000000000    0 0.00000000
  DDB_G0267182    0 0.000000000    0 0.03810585
  DDB_G0267184    0 0.000000000    0 0.00000000
  &gt; 
  
  I have converted expression matrix to a binary matrix by 2 as a threshold
  
  mat[mat &lt; 2] &lt;- 0
  mat[mat &gt; 2] &lt;- 1
  
  &gt; head(exp[1:4,1:4])
               s1.1 s1.2 s1.3 s1.4
  DDB_G0267382    0    0    0    1
  DDB_G0267438    0    0    0    1
  DDB_G0267466    0    0    0    0
  DDB_G0267476    0    0    1    0
  &gt; 
  &gt; exp=colSums(exp)
  &gt; exp=as.matrix(exp)
  &gt; colnames(exp)="value"
  &gt; exp=as.data.frame(exp)
  &gt; cc &lt;- AddMetaData(object = seurat, metadata = exp)
  &gt; cc &lt;- SetAllIdent(object = cc, id = "value")
  &gt; TSNEPlot(object = cc, do.return= TRUE)
  </code></pre>
  
  <p>How I can convert this range to a gradient of colours for example in 8-18, 18-28, 28-38, 38-48 range in blue to yellow please? Something like below</p>
  
  <p><a href="https://i.stack.imgur.com/Ph8xz.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/Ph8xz.png" alt="enter image description here"></a></p>
  
  <p>Thank you for any help</p>
  
  <p>Then by ggplot now I scaled my colours but I don't like my clusters as so and I don't know how to retain my clusters as a featureplot by this new color gradient </p>
  
  <pre><code>&gt; head(cc@meta.data)
       nGene    nUMI    orig.ident res.0.7 CELL STAGE GENO dataset stage.nice celltype value
  s1.1  4331  373762 SeuratProject       0 s1.1   H16   WT       1        H16        0    34
  s1.2  5603 1074639 SeuratProject       0 s1.2   H16   WT       1        H16        0    26
  s1.3  2064   49544 SeuratProject       0 s1.3   H16   WT       1        H16        0    27
  s1.4  4680  772399 SeuratProject       1 s1.4   H16   WT       1        H16        1    29
  s1.5  3876  272356 SeuratProject       1 s1.5   H16   WT       1        H16        1    21
  s1.6  2557  122314 SeuratProject       0 s1.6   H16   WT       1        H16        0    31
  
  &gt; ggplot(as.data.frame(cc@meta.data), aes(x = cc@meta.data<span class="math-container">$CELL, y = cc@meta.data$</span>res.0.7, colour =cc@meta.data$value)) + 
  +     geom_point(size = 5) +
  +     scale_colour_gradient(low = "yellow", high = "blue")
  </code></pre>
  
  <p><a href="https://i.stack.imgur.com/GtSTm.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/GtSTm.png" alt="enter image description here"></a></p>
  
  <p>By below code I obtained a tsne in link</p>
  
  <pre><code>&gt; cols &lt;-  scales::seq_gradient_pal(low="beige", high="red", space="Lab")(seq(from=0, to=1,length.out=48))
  &gt; 
  &gt; TSNEPlot(cc, colors.use=cols)
  </code></pre>
  
  <p><a href="https://image.ibb.co/mzpZ7f/Rplot21.png" rel="nofollow noreferrer">enter link description here</a></p>
  
  <p>Now I want to know how I could convert this range to a 8-18, 18-28, 28-38, 38-48 colour range as a gradient of blue to yellow?</p>
   181: <p><strong>TSNEPlot()</strong></p>
  
  <p><code>TSNEPlot()</code> will always treat your variables as discrete. My approach is to manually generate a gradient with unique colors for each factor level and pass it to the <code>cols.use</code> argument in <code>TSNEPlot()</code>. </p>
  
  <pre><code>#generate values for testing purposes, one value for each cell
  value &lt;- sample(seq(from=8, to=48, by=1), size = length(rownames(unfiltered_cca@meta.data)), replace=TRUE)
  names(value) &lt;- rownames(exp@meta.data)
  exp &lt;- AddMetaData(object=exp, metadata=value, col.name="value")
  exp &lt;-  SetIdent(exp, ident.use=exp@meta.data$value)
  #create a gradient between specified colors, multiply by sequence to get appropriate length
  #length.out is the number of different colors, number of factor levels
  cols &lt;-  scales::seq_gradient_pal(low="beige", high="red", space="Lab")(seq(from=0, to=1,length.out=48))
  
  
  TSNEPlot(exp, colors.use=cols)
  </code></pre>
  
  <p><a href="https://i.stack.imgur.com/PKps4.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/PKps4.png" alt="enter image description here"></a></p>
  
  <p>I would present this with no legend:</p>
  
  <pre><code>TSNEPlot(exp, colors.use=cols, no.legend = TRUE)
  </code></pre>
  
  <p><a href="https://i.stack.imgur.com/Ix0cj.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/Ix0cj.png" alt="enter image description here"></a></p>
  
  <p><strong>FeaturePlot()</strong></p>
  
  <p>You can also simply use <code>FeaturePlot()</code> instead of <code>TSNEPlot()</code> to visualize the gradient. Using the same data as above:</p>
  
  <pre><code>FeaturePlot(object = exp, features.plot = "value", reduction.use = "tsne", no.legend = FALSE, cols.use = c("beige", "red"))
  </code></pre>
  
  <p><a href="https://i.stack.imgur.com/hZCd4.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/hZCd4.png" alt="enter image description here"></a></p>
  
  <p>You ask for a continuous scale, but this is not what is shown in your second plot.  You have a different color for each discrete range of values. I assume here that you want a continuous gradient. To achieve something like the second plot you provided requires a different approach.</p>
   181: <p>If you would like to color discrete intervals on a gradient as opposed to having a continuous gradient (like your second plot), use this approach. </p>
  
  <p>It is similar to the approach in the answer I posted with the continuous scale, but we simply break up the continuous scale in to intervals and color them by these intervals.</p>
  
  <pre><code>#generate values for testing purposes, one value for each cell, add to object
  value &lt;- sample(seq(from=8, to=46, by=1), size = length(rownames(exp@meta.data)), replace=TRUE)
  exp &lt;- AddMetaData(object=exp, metadata=value, col.name="value")
  
  #encode the continuous values as factors, determined by the interval they fall in to
  value_breaks &lt;- cut(exp@meta.data$value, breaks = c(8,18,28,38,46), include.lowest=TRUE, right=FALSE)
  
  #name the breaks by cell so they can be added by AddMetaData(), add them
  names(value_breaks) &lt;- rownames(exp@meta.data)
  exp &lt;- AddMetaData(object=exp, metadata=value_breaks, col.name="value_breaks")
  
  exp &lt;-  SetIdent(exp, ident.use=exp@meta.data$value_breaks)
  
  #create a gradient between specified intervals
  #length.out is the number of different colors, number of factor levels
  cols &lt;- scales::seq_gradient_pal(low="blue", high="yellow", space="Lab")(seq(from=0, to=1,length.out=4))
  
  TSNEPlot(exp, colors.use=cols)
  </code></pre>
  
  <p><a href="https://i.stack.imgur.com/lyXKc.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/lyXKc.png" alt="intervals colored"></a></p>
  
  <p>The label in the legend are classic mathematical notation for intervals. You can add your own labels if you wish in the <code>cut()</code> function.</p>
  