Answers.Body: <p>Assuming you're looking for <em>differential</em> expression values, the <code>FindMarkers</code> function within Seurat would be a good thing to try first:</p>
  <pre><code># find all markers distinguishing cluster 5 from clusters 0 and 3
  cluster5.markers &lt;- FindMarkers(pbmc, ident.1 = 5, ident.2 = c(0, 3), min.pct = 0.25)
  head(cluster5.markers, n = 5)
  ##                       p_val avg_log2FC pct.1 pct.2     p_val_adj
  ## FCGR3A        8.246578e-205   4.261495 0.975 0.040 1.130936e-200
  ## IFITM3        1.677613e-195   3.879339 0.975 0.049 2.300678e-191
  ## CFD           2.401156e-193   3.405492 0.938 0.038 3.292945e-189
  ## CD68          2.900384e-191   3.020484 0.926 0.035 3.977587e-187
  ## RP11-290F20.3 2.513244e-186   2.720057 0.840 0.017 3.446663e-182 
  </code></pre>
  <p>[Note the <code>avg_log2FC</code> column]</p>
  <p>More details can be found at the bottom of the Seurat tutorial pages for the PBMC 3K Guided Tutorial, <em>Finding differentially expressed features (cluster biomarkers)</em>:</p>
  <p><a href="https://satijalab.org/seurat/articles/pbmc3k_tutorial.html" rel="nofollow noreferrer">https://satijalab.org/seurat/articles/pbmc3k_tutorial.html</a></p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2023-02-27T00:40:13.630Z
Answers.Text: Thanks you very much! Yes, that is what I was looking for. I also found the AverageExpression function to look at expression values across clusters
Answers.UserDisplayName: Ahmed M.
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2023-02-24T18:55:13.363Z
Answers.LastActivityDate: 2023-02-24T18:55:13.363Z
Answers.UserDisplayName: gringer
Body: <p>I am analyzing publically available scRNA seq datasets on R using Seurat. I have created a seurat object, clustered and annotated different cell types. Now, I am interested in comparing the expression values and percentage of expressing cells within each cluster for a given set of genes I am interested in. I can  visualize their expression using DotPlots, feature plots, etc... but how can I generate a table with the expression values (log2FC) for my defined set of genes across the different clusters/cell types?
  Thanks!</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2023-02-23T18:39:53.633Z
Comments.Text: Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking.
Comments.UserDisplayName: Community
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2023-02-24T18:47:31.387Z
Comments.Text: Please clarify more precisely what you want, as there is inconsistency in your question. `log2FC` values are log-transformed fold change values, and represent a *change* between two expression profiles, i.e. they represent *differential* expression, not expression.
Comments.UserDisplayName: gringer
Tags: <scrnaseq><seurat><gene-expression>
Title: Determine expression values for a defined list of genes across different clusters in scRNA data using seurat
ThreadText: # Determine expression values for a defined list of genes across different clusters in scRNA data using seurat
  
  (Asked by: username_0 on 2023-02-23)
  
  I am analyzing publically available scRNA seq datasets on R using Seurat. I have created a seurat object, clustered and annotated different cell types. Now, I am interested in comparing the expression values and percentage of expressing cells within each cluster for a given set of genes I am interested in. I can visualize their expression using DotPlots, feature plots, etc... but how can I generate a table with the expression values (log2FC) for my defined set of genes across the different clusters/cell types?
  Thanks!
  
  **Tags:** scrnaseq, seurat, gene-expression
  
  > **Comments:**
  > **username_1**: Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking.  
  > **username_2**: Please clarify more precisely what you want, as there is inconsistency in your question. `log2FC` values are log-transformed fold change values, and represent a *change* between two expression profiles, i.e. they represent *differential* expression, not expression.  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_2 on 2023-02-24. Score: 1
  
  Assuming you're looking for *differential* expression values, the `FindMarkers` function within Seurat would be a good thing to try first:
  
  ```
  # find all markers distinguishing cluster 5 from clusters 0 and 3
  cluster5.markers <- FindMarkers(pbmc, ident.1 = 5, ident.2 = c(0, 3), min.pct = 0.25)
  head(cluster5.markers, n = 5)
  ##                       p_val avg_log2FC pct.1 pct.2     p_val_adj
  ## FCGR3A        8.246578e-205   4.261495 0.975 0.040 1.130936e-200
  ## IFITM3        1.677613e-195   3.879339 0.975 0.049 2.300678e-191
  ## CFD           2.401156e-193   3.405492 0.938 0.038 3.292945e-189
  ## CD68          2.900384e-191   3.020484 0.926 0.035 3.977587e-187
  ## RP11-290F20.3 2.513244e-186   2.720057 0.840 0.017 3.446663e-182 
  
  ```
  
  [Note the `avg_log2FC` column]
  
  More details can be found at the bottom of the Seurat tutorial pages for the PBMC 3K Guided Tutorial, *Finding differentially expressed features (cluster biomarkers)*:
  
  <https://satijalab.org/seurat/articles/pbmc3k_tutorial.html>
  
  > **Comments:**
  > **username_0**: Thanks you very much! Yes, that is what I was looking for. I also found the AverageExpression function to look at expression values across clusters  
  
  ---
  
  