Answers.Body: <p>The thing to tweak is the <code>group.by</code> argument of the <code>Dimplot</code> function.</p>
  <p>It looks like you've already tried this in your attempts at solving <a href="https://bioinformatics.stackexchange.com/questions/16332/color-by-clusters-and-sampled-in-seurat">a different problem</a>.</p>
  <p>The main thing you need to be aware of is that each new clustering needs to be saved as a separate metadata variable in order to do this. As I mentioned in one of my <a href="https://bioinformatics.stackexchange.com/a/16337/73">previous answers</a>, I like to use the <code>[[X]]</code> notation for this:</p>
  <pre><code>control[[&quot;predicted.celltype.l1&quot;]] &lt;- a<span class="math-container">$predicted.celltype.l1
  control[["predicted.celltype.l2"]] &lt;- a$</span>predicted.celltype.l2
  </code></pre>
  <p>Then you should be able to use both in the <code>group.by</code> argument:</p>
  <pre><code>DimPlot(control, reduction = &quot;umap&quot;, group.by = &quot;predicted.celltype.l1&quot;)
  DimPlot(control, reduction = &quot;umap&quot;, group.by = &quot;predicted.celltype.l2&quot;)
  </code></pre>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-07-15T12:08:41.263Z
Answers.LastActivityDate: 2021-07-15T23:05:39.110Z
Answers.LastEditDate: 2021-07-15T23:05:39.110Z
Answers.UserDisplayName: gringer
Body: <p>In Seurat metadata I have assigned cells to some cell types with different resolutions</p>
  <p>I have added the cluster identities to the object via <code>Idents</code>:</p>
  <pre><code> Idents(control) &lt;- a$predicted.celltype.l1
  </code></pre>
  <p><a href="https://i.sstatic.net/xoWPp.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/xoWPp.png" alt="enter image description here" /></a></p>
  <p>I then added another clustering in the same way:</p>
  <pre><code> Idents(control) &lt;- a$predicted.celltype.l2
  </code></pre>
  <p>Dimplot will now show the new identities:</p>
  <p><a href="https://i.sstatic.net/XpReN.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/XpReN.png" alt="enter image description here" /></a></p>
  <p>How I can ask Dimplot to plot the clustering I want for example if I want to show <code>predicted.celltype.l1</code> again (something like changing the default)?</p>
  
Tags: <scrnaseq><seurat><10x-genomics>
Title: Seurat Dimplot with different clustering IDs
ThreadText: # Seurat Dimplot with different clustering IDs
  
  (Asked by: username_0 on 2021-07-15)
  
  In Seurat metadata I have assigned cells to some cell types with different resolutions
  
  I have added the cluster identities to the object via `Idents`:
  
  ```
   Idents(control) <- a$predicted.celltype.l1
  
  ```
  
  [![enter image description here](https://i.sstatic.net/xoWPp.png)](https://i.sstatic.net/xoWPp.png)
  
  I then added another clustering in the same way:
  
  ```
   Idents(control) <- a$predicted.celltype.l2
  
  ```
  
  Dimplot will now show the new identities:
  
  [![enter image description here](https://i.sstatic.net/XpReN.png)](https://i.sstatic.net/XpReN.png)
  
  How I can ask Dimplot to plot the clustering I want for example if I want to show `predicted.celltype.l1` again (something like changing the default)?
  
  **Tags:** scrnaseq, seurat, 10x-genomics
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2021-07-15. Score: 1 | Accepted answer
  
  The thing to tweak is the `group.by` argument of the `Dimplot` function.
  
  It looks like you've already tried this in your attempts at solving [a different problem](https://bioinformatics.stackexchange.com/questions/16332/color-by-clusters-and-sampled-in-seurat).
  
  The main thing you need to be aware of is that each new clustering needs to be saved as a separate metadata variable in order to do this. As I mentioned in one of my [previous answers](https://bioinformatics.stackexchange.com/a/16337/73), I like to use the `[[X]]` notation for this:
  
  ```
  control[["predicted.celltype.l1"]] <- a$predicted.celltype.l1
  control[["predicted.celltype.l2"]] <- a$predicted.celltype.l2
  
  ```
  
  Then you should be able to use both in the `group.by` argument:
  
  ```
  DimPlot(control, reduction = "umap", group.by = "predicted.celltype.l1")
  DimPlot(control, reduction = "umap", group.by = "predicted.celltype.l2")
  
  ```
  
  
  ---
  
  