Answers.Body: <p>Directly copy-pasting from <a href="https://satijalab.org/seurat/articles/pbmc3k_tutorial.html" rel="nofollow noreferrer">one of the Seurat vignettes</a>:</p>
  <pre><code># find markers for every cluster compared to all remaining cells, report only the positive ones
  pbmc.markers &lt;- FindAllMarkers(pbmc, only.pos = TRUE, min.pct = 0.25, logfc.threshold = 0.25)
  pbmc.markers %&gt;%
      group_by(cluster) %&gt;%
      top_n(n = 2, wt = avg_log2FC)
  </code></pre>
  <p>Change <code>n</code> to 10 in the <code>top_n()</code> call and filter for your cluster of interest and you will get what you want.</p>
  
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Answers.CreationDate: 2021-06-11T07:47:25.340Z
Answers.Text: Thanks a lot,  I realized this code exist in seurat web page, but I didn't know that does the same. Thanks for answering.
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Body: <p>I detected all markers for each cluster and checked 20 top markers for my clusters one by one. Is there any way that I figure out the selective markers automatically from all the clusters?</p>
  <p>For instance, in seurat tutorial, I found comparing one cluster two or three other clusters, but I want to see for instance what are the 10 top markers or genes that are expressed only in cluster of interest.</p>
  
Tags: <seurat><clustering>
Title: Find selective markers for one cluster automatically
ThreadText: # Find selective markers for one cluster automatically
  
  (Asked by: username_0 on 2021-06-09)
  
  I detected all markers for each cluster and checked 20 top markers for my clusters one by one. Is there any way that I figure out the selective markers automatically from all the clusters?
  
  For instance, in seurat tutorial, I found comparing one cluster two or three other clusters, but I want to see for instance what are the 10 top markers or genes that are expressed only in cluster of interest.
  
  **Tags:** seurat, clustering
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2021-06-10. Score: 2 | Accepted answer
  
  Directly copy-pasting from [one of the Seurat vignettes](https://satijalab.org/seurat/articles/pbmc3k_tutorial.html):
  
  ```
  # find markers for every cluster compared to all remaining cells, report only the positive ones
  pbmc.markers <- FindAllMarkers(pbmc, only.pos = TRUE, min.pct = 0.25, logfc.threshold = 0.25)
  pbmc.markers %>%
      group_by(cluster) %>%
      top_n(n = 2, wt = avg_log2FC)
  
  ```
  
  Change `n` to 10 in the `top_n()` call and filter for your cluster of interest and you will get what you want.
  
  > **Comments:**
  > **username_0**: Thanks a lot,  I realized this code exist in seurat web page, but I didn't know that does the same. Thanks for answering.  
  
  ---
  
  