Answers.Body: <p>Checkout the first <a href="https://satijalab.org/seurat/articles/pbmc3k_tutorial.html" rel="nofollow noreferrer">Seurat tutorial</a>. To filter cells with &gt;20% mitochondrial counts:</p>
  <pre><code>obj[[&quot;percent.mito&quot;]] &lt;- PercentageFeatureSet(obj, pattern = &quot;^MT-&quot;)
  obj &lt;- subset(obj, subset = percent.mito &lt; 20)
  </code></pre>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-07-16T16:42:08.270Z
Answers.Text: I tried reading the tutorial and things are not really clear there. @Exhausted, when the tutorial says "we filter cells", they mean filtering them out i.e. removing them. So in the `subset` call, one needs to state the criteria that the data needs to pass. It's quite clear that the percent is 1-100, not 0-1 though.
Answers.UserDisplayName: Ram RS
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-07-15T20:57:29.390Z
Answers.LastActivityDate: 2021-07-15T20:57:29.390Z
Answers.UserDisplayName: Chris_Rands
Body: <p>I have extensively read about <code>percent mito</code> in Seurat but I got more and more confused</p>
  <p>Let's say we want to keep cells with <code>maximum 20%</code> of their expressed genes are mitochondrial genes, so shall I set <code>percent.mito &lt; 20</code> or <code>percent.mito &lt; 0.2</code> or <code>percent.mito &lt; 80</code> ?</p>
  
Tags: <scrnaseq><seurat><10x-genomics>
Title: What does this Seurat argument mean
ThreadText: # What does this Seurat argument mean
  
  (Asked by: username_0 on 2021-07-15)
  
  I have extensively read about `percent mito` in Seurat but I got more and more confused
  
  Let's say we want to keep cells with `maximum 20%` of their expressed genes are mitochondrial genes, so shall I set `percent.mito < 20` or `percent.mito < 0.2` or `percent.mito < 80` ?
  
  **Tags:** scrnaseq, seurat, 10x-genomics
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2021-07-15. Score: 2 | Accepted answer
  
  Checkout the first [Seurat tutorial](https://satijalab.org/seurat/articles/pbmc3k_tutorial.html). To filter cells with >20% mitochondrial counts:
  
  ```
  obj[["percent.mito"]] <- PercentageFeatureSet(obj, pattern = "^MT-")
  obj <- subset(obj, subset = percent.mito < 20)
  
  ```
  
  > **Comments:**
  > **username_2**: I tried reading the tutorial and things are not really clear there. @Exhausted, when the tutorial says "we filter cells", they mean filtering them out i.e. removing them. So in the `subset` call, one needs to state the criteria that the data needs to pass. It's quite clear that the percent is 1-100, not 0-1 though.  
  
  ---
  
  