Body: <p>I have different treatments (infected and control ones). When using DESeq2, I have different results in two ways of comparison.
  first way:</p>
  <p>factor: treatment, factor level1: Moribund Infected, factor level2: 5week Infected, factor level3: Moribund Control, factor level4: 5week Control.
  I have 6 result files (comparisons among factor levels)</p>
  <p>second way: (I compared just 2 groups to each other)</p>
  <pre><code>factor: treatment, factor level1: Moribund Infected, factor level2: 5week Infected.
  factor: treatment, factor level1: Moribund Infected, factor level2: Moribund Control.
  factor: treatment, factor level1: Moribund Infected, factor level2:the  5week Control.
  factor: treatment, factor level1: 5week Infected, factor level2: Moribund Control.
  factor: treatment, factor level1: 5week Infected, factor level2: 5week Control.
  factor: treatment, factor level 1: Moribund Control, factor level2: 5week Control.
  </code></pre>
  <p>Finally, the results were different in these two ways of comparison. I have more significantly expressed genes in most comparisons of first way and even I have few comparisons in the second way that have more significantly expressed genes.</p>
  <p>Why and which way is trustable?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-05-19T01:10:36.483Z
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: 2022-05-19T01:58:44.283Z
Comments.Text: Could you please show the specific design formulas you used to describe the statistical models in the DESeq2 commands. Showing the full factor table would be helpful as well (e.g. `colData` in the DESeq2 commands).
Comments.UserDisplayName: gringer
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-05-19T19:38:52.873Z
Comments.Text: Cross-posted:https://support.bioconductor.org/p/9144330/
Comments.UserDisplayName: swbarnes2
Tags: <deseq2>
Title: Different results of DESeq2 in different ways of comparison
ThreadText: # Different results of DESeq2 in different ways of comparison
  
  (Asked by: username_0 on 2022-05-18)
  
  I have different treatments (infected and control ones). When using DESeq2, I have different results in two ways of comparison.
  first way:
  
  factor: treatment, factor level1: Moribund Infected, factor level2: 5week Infected, factor level3: Moribund Control, factor level4: 5week Control.
  I have 6 result files (comparisons among factor levels)
  
  second way: (I compared just 2 groups to each other)
  
  ```
  factor: treatment, factor level1: Moribund Infected, factor level2: 5week Infected.
  factor: treatment, factor level1: Moribund Infected, factor level2: Moribund Control.
  factor: treatment, factor level1: Moribund Infected, factor level2:the  5week Control.
  factor: treatment, factor level1: 5week Infected, factor level2: Moribund Control.
  factor: treatment, factor level1: 5week Infected, factor level2: 5week Control.
  factor: treatment, factor level 1: Moribund Control, factor level2: 5week Control.
  
  ```
  
  Finally, the results were different in these two ways of comparison. I have more significantly expressed genes in most comparisons of first way and even I have few comparisons in the second way that have more significantly expressed genes.
  
  Why and which way is trustable?
  
  **Tags:** deseq2
  
  > **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**: Could you please show the specific design formulas you used to describe the statistical models in the DESeq2 commands. Showing the full factor table would be helpful as well (e.g. `colData` in the DESeq2 commands).  
  > **username_3**: Cross-posted:https://support.bioconductor.org/p/9144330/  
  
  ---
  
  ## 0 answers
  
  