text: user17068: 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!
  
  user73: 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
  
original_text: 17068: <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>
   73: <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>
  