text: user16412: I am new to using both DESeq2 and EdgeR in Bioconductor used for transforming my RNA expression data.
  However, I am struggling to understand their specific purpose, differences between them and underlying theory. The information is required for a thesis with an imminent deadline
  
  user14212: I think your question has been answered very well here:
  https://www.biostars.org/p/284775/
  If you want to go deeper perhaps you can look at this paper by Li et al.
  https://genomebiology.biomedcentral.com/articles/10.1186/s13059-022-02648-4
  where they argue that for large scale datasets (multiple conditions) both of these methods are not optimal and instead suggests using Wilcoxon rank-sum test to decrease chances of FDRs.
  Best,
  av
  
original_text: 16412: <p>I am new to using both DESeq2 and EdgeR in Bioconductor used for transforming my RNA expression data.</p>
  <p>However, I am struggling to understand their specific purpose, differences between them and underlying theory. The information is required for a thesis with an imminent deadline</p>
   14212: <p>I think your question has been answered very well here:
  <a href="https://www.biostars.org/p/284775/" rel="nofollow noreferrer">https://www.biostars.org/p/284775/</a></p>
  <p>If you want to go deeper perhaps you can look at this paper by Li et al.
  <a href="https://genomebiology.biomedcentral.com/articles/10.1186/s13059-022-02648-4" rel="nofollow noreferrer">https://genomebiology.biomedcentral.com/articles/10.1186/s13059-022-02648-4</a>
  where they argue that for large scale datasets (multiple conditions) both of these methods are not optimal and instead suggests using Wilcoxon rank-sum test to decrease chances of FDRs.</p>
  <p>Best,</p>
  <p>av</p>
  