Answers.Body: <ol>
  <li><p><code>pct.1</code>– The percentage of cells where the gene is detected in the first group</p>
  </li>
  <li><p><code>p_val_adj</code>– Adjusted p-value, based on bonferroni correction using all genes in the dataset.</p>
  </li>
  </ol>
  <blockquote>
  <p>This is <strong>not</strong> also known as a false discovery rate (FDR) adjusted p-value.</p>
  </blockquote>
  <p>An adjusted p-value of 1.00 means that after correcting for multiple testing, there is a 100% chance that the result (the logFC here) is due to chance.</p>
  <ol start="3">
  <li>You are correct. The expression of <code>Cttnbp2</code> donwn-regulated by that factor. If you were to look in the table at the cluster 1 DE genes you would see <code>Cttnbp2</code> with a logFC value of 1.35264. When you are looking at genes differentailly expressed in only two clusters, the sign is the only thing that changes.</li>
  </ol>
  <p><a href="https://satijalab.org/seurat/de_vignette.html" rel="nofollow noreferrer">Vignette</a> posted above by @heathobrien.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-08-16T13:51:01.083Z
Answers.Text: How the adjusted p-value is computed depends on on the method used (`use.test`). E.g. `"DESeq2"` uses Independent Hypothesis Weighting. While Bonferroni correction does indeed control the FDR as a side effect it is build to control the family-wise error error rate. An adjusted p-value of 1 does not mean that the result is due to chance, it just means that it cannot be excluded (by the methods used) that such a difference would be observed was there no true difference in expression.
Answers.UserDisplayName: jan-glx
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2018-07-02T20:18:58.300Z
Answers.LastActivityDate: 2021-11-20T06:31:08.733Z
Answers.LastEditDate: 2021-11-20T06:31:08.733Z
Answers.UserDisplayName: Kohl Kinning
Body: <p>I compared two manually defined clusters using <code>Seurat</code> package function <code>FindAllMarkers</code> and got the output:</p>
  
  <p><a href="https://i.sstatic.net/yja4Q.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/yja4Q.png" alt="enter image description here"></a></p>
  
  <p>Now, I am confused about three things:</p>
  
  <ol>
  <li>What are <code>pct.1</code> and <code>pct.2</code>?</li>
  <li>How come <code>p-adjusted values</code> equal to <code>1</code>? What does it mean?</li>
  <li>If we take first row, what does <code>avg_logFC</code> value of <code>-1.35264</code> mean when we have cluster <code>0</code> in the <code>cluster</code> column? Is it that in cluster <code>0</code> the <code>Cttnbp2</code> gene downregulated by a factor of <code>2^1.35264</code>?</li>
  </ol>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-05-09T06:36:20.070Z
Comments.Text: https://satijalab.org/seurat/de_vignette.html
Comments.UserDisplayName: heathobrien
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-05-09T09:53:42.597Z
Comments.Text: You have a few questions (like this one) that could have been answered with some simple googling. I suggest you try that first before posting here.
Comments.UserDisplayName: Devon Ryan
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-05-09T18:18:51.047Z
Comments.Text: I could not find it, that's why I posted. Thank you @heathobrien! Should I remove the Q?
Comments.UserDisplayName: Nikita Vlasenko
Tags: <r><seurat>
Title: Output of Seurat FindAllMarkers parameters
ThreadText: # Output of Seurat FindAllMarkers parameters
  
  (Asked by: username_0 on 2018-05-09)
  
  I compared two manually defined clusters using `Seurat` package function `FindAllMarkers` and got the output:
  
  [![enter image description here](https://i.sstatic.net/yja4Q.png)](https://i.sstatic.net/yja4Q.png)
  
  Now, I am confused about three things:
  
  1. What are `pct.1` and `pct.2`?
  2. How come `p-adjusted values` equal to `1`? What does it mean?
  3. If we take first row, what does `avg_logFC` value of `-1.35264` mean when we have cluster `0` in the `cluster` column? Is it that in cluster `0` the `Cttnbp2` gene downregulated by a factor of `2^1.35264`?
  
  **Tags:** r, seurat
  
  > **Comments:**
  > **username_1**: https://satijalab.org/seurat/de_vignette.html  
  > **username_2**: You have a few questions (like this one) that could have been answered with some simple googling. I suggest you try that first before posting here.  
  > **username_0**: I could not find it, that's why I posted. Thank you @username_1! Should I remove the Q?  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_3 on 2018-07-02. Score: 3 | Accepted answer
  
  1. `pct.1`– The percentage of cells where the gene is detected in the first group
  2. `p_val_adj`– Adjusted p-value, based on bonferroni correction using all genes in the dataset.
  
  > This is **not** also known as a false discovery rate (FDR) adjusted p-value.
  
  An adjusted p-value of 1.00 means that after correcting for multiple testing, there is a 100% chance that the result (the logFC here) is due to chance.
  
  3. You are correct. The expression of `Cttnbp2` donwn-regulated by that factor. If you were to look in the table at the cluster 1 DE genes you would see `Cttnbp2` with a logFC value of 1.35264. When you are looking at genes differentailly expressed in only two clusters, the sign is the only thing that changes.
  
  [Vignette](https://satijalab.org/seurat/de_vignette.html) posted above by @username_1.
  
  > **Comments:**
  > **username_4**: How the adjusted p-value is computed depends on on the method used (`use.test`). E.g. `"DESeq2"` uses Independent Hypothesis Weighting. While Bonferroni correction does indeed control the FDR as a side effect it is build to control the family-wise error error rate. An adjusted p-value of 1 does not mean that the result is due to chance, it just means that it cannot be excluded (by the methods used) that such a difference would be observed was there no true difference in expression.  
  
  ---
  
  