Answers.Body: <p>A <em>gene set enrichment analysis</em> (GSEA) tests for <em>enrichment</em> of a gene set within a ranked list of genes.</p>
  <p>The primary outcome of the analysis is <em>enrichment</em> or <em>no enrichment</em>. Gene sets frequently include correlated genes, and that correlation can be positive (enhancers or co-expressors) or negative (e.g repressors). It's reasonable to include negatively-correlated genes within gene sets because some pathways involve both enhancement of a particular biochemical pathway, and suppression of a pathway that carries out opposite things.</p>
  <p>I don't know about the KRAS pathway you're comparing against here, but a statement I would make based on interpreting that GSEA graph would be something like, &quot;The KRAS.600_UP.V1_DN gene set is enriched when comparing the expression of responders vs non-responders.&quot;</p>
  <p>I'm not quite sure how you separated up and down-regulated genes (code would be helpful with that). Your down regulated gene plot looks like it's ranked in the opposite direction to the combined plot, which is not what I expect. I think that determining an enrichment score separately for upregulated and downregulated genes (within your ranked list of genes) is a good idea, but it shouldn't change the direction of the enrichment curve within each category. It will, however, alter the form of the curve, by stretching or compressing values vertically and altering the start/end offset.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-05-23T12:59:58.853Z
Answers.LastActivityDate: 2021-05-23T13:09:18.437Z
Answers.LastEditDate: 2021-05-23T13:09:18.437Z
Answers.UserDisplayName: gringer
Answers.Body: <p>In Deseq2, it depends on contrast eg. if your <code>contrast &lt;- c(&quot;Condition&quot;, firstC, SecondC)</code> is then <code>-ve</code> is downregulated in <code>FirstC</code> and same for <code>+ve</code>. It is always better to take look at count data for the confirmation (responders versus non-responders samples).</p>
  <p>[for more detail you can refer here][1]</p>
  <p>[1]<a href="https://github.com/amarinderthind/RNA-seq-tutorial-for-gene-differential-expression-analysis/blob/master/RNA-Seq-DGE.R" rel="nofollow noreferrer">https://github.com/amarinderthind/RNA-seq-tutorial-for-gene-differential-expression-analysis/blob/master/RNA-Seq-DGE.R</a></p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-08-11T05:34:53.607Z
Answers.LastActivityDate: 2021-05-24T13:07:59.537Z
Answers.LastEditDate: 2021-05-24T13:07:59.537Z
Answers.UserDisplayName: Amarinder Singh Thind
Body: <p>I have <code>RNA-seq</code> for two groups of patients: <code>Responders</code> to chemotherapy (n=9) versus <code>non-responders</code> to chemotherapy (n=24)</p>
  <p>I have done <code>DESeq2</code> and obtain <code>fold change of responders versus non-responders</code> in which <code>positive fold change</code> means <code>down-regulation in responders</code> (if I am not wrong)</p>
  <pre><code>&gt; head(df)
      gene       FC
  1 286499 7.116071
  2 260436 6.691189
  3   2267 5.751322
  4   5968 5.522079
  5   4103 5.328008
  6 442709 5.036087
  &gt; 
  </code></pre>
  <p>I have done <code>GSEA</code> in <code>pre-ranked</code> way</p>
  <p>got this plot for <code>KRAS pathway</code></p>
  <p><a href="https://i.sstatic.net/mwPGW.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/mwPGW.png" alt="enter image description here" /></a></p>
  <p>I interpret this as; <code>KRAS pathway</code> in being <code>down regulated</code> in <code>responders</code></p>
  <p>Am I right?</p>
  <p>Please correct me</p>
  <p>When I separated genes for up and down regulated</p>
  <p>For up regulated genes I did not get any significant GSEA but for down regulated genes in responders I got this</p>
  <p><a href="https://i.sstatic.net/Rq30k.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/Rq30k.png" alt="enter image description here" /></a></p>
  <p>SO does this mean that <code>KRAS pathway</code> is being <code>up regulated</code> in <code>responders</code> because I have used <code>down regulated genes in responders</code>?</p>
  
Tags: <r><rna-seq><pathway><gsea>
Title: Interpreting this plot from GSEA
ThreadText: # Interpreting this plot from GSEA
  
  (Asked by: username_0 on 2020-08-10)
  
  I have `RNA-seq` for two groups of patients: `Responders` to chemotherapy (n=9) versus `non-responders` to chemotherapy (n=24)
  
  I have done `DESeq2` and obtain `fold change of responders versus non-responders` in which `positive fold change` means `down-regulation in responders` (if I am not wrong)
  
  ```
  > head(df)
      gene       FC
  1 286499 7.116071
  2 260436 6.691189
  3   2267 5.751322
  4   5968 5.522079
  5   4103 5.328008
  6 442709 5.036087
  > 
  
  ```
  
  I have done `GSEA` in `pre-ranked` way
  
  got this plot for `KRAS pathway`
  
  [![enter image description here](https://i.sstatic.net/mwPGW.png)](https://i.sstatic.net/mwPGW.png)
  
  I interpret this as; `KRAS pathway` in being `down regulated` in `responders`
  
  Am I right?
  
  Please correct me
  
  When I separated genes for up and down regulated
  
  For up regulated genes I did not get any significant GSEA but for down regulated genes in responders I got this
  
  [![enter image description here](https://i.sstatic.net/Rq30k.png)](https://i.sstatic.net/Rq30k.png)
  
  SO does this mean that `KRAS pathway` is being `up regulated` in `responders` because I have used `down regulated genes in responders`?
  
  **Tags:** r, rna-seq, pathway, gsea
  
  
  ---
  
  ## 2 answers
  
  ### Answer by username_1 on 2021-05-23. Score: 1 | Accepted answer
  
  A *gene set enrichment analysis* (GSEA) tests for *enrichment* of a gene set within a ranked list of genes.
  
  The primary outcome of the analysis is *enrichment* or *no enrichment*. Gene sets frequently include correlated genes, and that correlation can be positive (enhancers or co-expressors) or negative (e.g repressors). It's reasonable to include negatively-correlated genes within gene sets because some pathways involve both enhancement of a particular biochemical pathway, and suppression of a pathway that carries out opposite things.
  
  I don't know about the KRAS pathway you're comparing against here, but a statement I would make based on interpreting that GSEA graph would be something like, "The KRAS.600\_UP.V1\_DN gene set is enriched when comparing the expression of responders vs non-responders."
  
  I'm not quite sure how you separated up and down-regulated genes (code would be helpful with that). Your down regulated gene plot looks like it's ranked in the opposite direction to the combined plot, which is not what I expect. I think that determining an enrichment score separately for upregulated and downregulated genes (within your ranked list of genes) is a good idea, but it shouldn't change the direction of the enrichment curve within each category. It will, however, alter the form of the curve, by stretching or compressing values vertically and altering the start/end offset.
  
  
  ---
  
  ### Answer by username_2 on 2020-08-11. Score: 1
  
  In Deseq2, it depends on contrast eg. if your `contrast <- c("Condition", firstC, SecondC)` is then `-ve` is downregulated in `FirstC` and same for `+ve`. It is always better to take look at count data for the confirmation (responders versus non-responders samples).
  
  [for more detail you can refer here][1]
  
  [1]<https://github.com/amarinderthind/RNA-seq-tutorial-for-gene-differential-expression-analysis/blob/master/RNA-Seq-DGE.R>
  
  
  ---
  
  