Answers.Body: <p><strong>August 2021</strong></p>
  <p>To date, it seems that the response to this question is <strong>&quot;No&quot;</strong>. However, there is a GitHub repository called <a href="https://github.com/r-bioinformatics/edgePy" rel="nofollow noreferrer"><code>edgePy</code></a>, aiming to <em>&quot;become an implementation of <a href="https://bioconductor.org/packages/release/bioc/html/edgeR.html" rel="nofollow noreferrer"><code>edgeR</code></a> for differential expression analysis in the Python language&quot;</em> (<code>edgeR</code> is somewhat similar to <code>limma</code>).</p>
  <p>PS: Many thanks to @ATpoint90 (the Twitter <a href="https://twitter.com/ATpoint90/status/1423669033702940678" rel="nofollow noreferrer">&quot;hive mind&quot; summoner</a>) and @sridnona6 (<code>edgePy</code> developer).</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-08-07T18:08:00.623Z
Answers.LastActivityDate: 2021-08-11T01:37:57.120Z
Answers.LastEditDate: 2021-08-11T01:37:57.120Z
Answers.UserDisplayName: Gian Arauz
Body: <p>The R package <a href="https://bioconductor.org/packages/release/bioc/html/limma.html" rel="nofollow noreferrer"><code>limma</code></a> is ideal to perform differential expression analysis. Is there any <code>limma</code> alternative in Python?</p>
  <p>I'm trying to use <a href="https://www.statsmodels.org/stable/index.html" rel="nofollow noreferrer"><code>statsmodels</code></a> and <a href="https://scikit-learn.org/stable/" rel="nofollow noreferrer"><code>scikitlearn</code></a> in conjunction with some other cool tools (such as <a href="https://github.com/epigenelabs/pyComBat" rel="nofollow noreferrer"><code>pycombat</code></a>) to get <code>limma</code>-like workflows. However, I'm missing many capabilities from the <code>limma</code> toolbox.</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-08-11T06:24:36.823Z
Comments.Text: Is there a possibility for you to call R from Python? If so you can try Rpy2 (https://pypi.org/project/rpy2/)
Comments.UserDisplayName: jxx_fa
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-08-11T08:44:47.447Z
Comments.Text: That's true. You can always wrap Python around R. For example, if working with `limma`, you can use Python to prepare the pieces that `limma` needs to create an Expression Set object with the `ExpressionSet()` function (expression, phenotype and feature data). However you will be always forced to write the `limma` workflow using R syntax. In any case I will give it a try! Many Thanks!
Comments.UserDisplayName: Gian Arauz
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-02-18T17:27:03.243Z
Comments.Text: I am working on EXACTLY this thing. My `methylize` python package supports some of these functions, but I found this while looking for packages that might give me idea about what features people want.
Comments.UserDisplayName: Marc Maxmeister
Tags: <r><python><differential-expression><limma>
Title: R limma alternatives in Python
ThreadText: # R limma alternatives in Python
  
  (Asked by: username_0 on 2021-08-06)
  
  The R package [`limma`](https://bioconductor.org/packages/release/bioc/html/limma.html) is ideal to perform differential expression analysis. Is there any `limma` alternative in Python?
  
  I'm trying to use [`statsmodels`](https://www.statsmodels.org/stable/index.html) and [`scikitlearn`](https://scikit-learn.org/stable/) in conjunction with some other cool tools (such as [`pycombat`](https://github.com/epigenelabs/pyComBat)) to get `limma`-like workflows. However, I'm missing many capabilities from the `limma` toolbox.
  
  **Tags:** r, python, differential-expression, limma
  
  > **Comments:**
  > **username_1**: Is there a possibility for you to call R from Python? If so you can try Rpy2 (https://pypi.org/project/rpy2/)  
  > **username_0**: That's true. You can always wrap Python around R. For example, if working with `limma`, you can use Python to prepare the pieces that `limma` needs to create an Expression Set object with the `ExpressionSet()` function (expression, phenotype and feature data). However you will be always forced to write the `limma` workflow using R syntax. In any case I will give it a try! Many Thanks!  
  > **username_2**: I am working on EXACTLY this thing. My `methylize` python package supports some of these functions, but I found this while looking for packages that might give me idea about what features people want.  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_0 on 2021-08-07. Score: 2 | Accepted answer
  
  **August 2021**
  
  To date, it seems that the response to this question is **"No"**. However, there is a GitHub repository called [`edgePy`](https://github.com/r-bioinformatics/edgePy), aiming to *"become an implementation of [`edgeR`](https://bioconductor.org/packages/release/bioc/html/edgeR.html) for differential expression analysis in the Python language"* (`edgeR` is somewhat similar to `limma`).
  
  PS: Many thanks to @ATpoint90 (the Twitter ["hive mind" summoner](https://twitter.com/ATpoint90/status/1423669033702940678)) and @sridnona6 (`edgePy` developer).
  
  
  ---
  
  