Answers.Body: <p>I guess it is too late to answer this now, but I think you can use <code>gseapy</code>. Its a <code>python</code> module for performing enrichment analysis. Just install it with:</p>
  <blockquote>
  <p><code>pip install gseapy</code></p>
  </blockquote>
  <p>There is also a tutorial of sorts on <code>Medium</code>
  <a href="https://medium.com/omics-diary/how-to-use-gseapy-for-pathway-enrichment-analysis-67a1aab1002d" rel="nofollow noreferrer">https://medium.com/omics-diary/how-to-use-gseapy-for-pathway-enrichment-analysis-67a1aab1002d</a>.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-07-17T17:24:37.270Z
Answers.LastActivityDate: 2024-07-17T17:24:37.270Z
Answers.UserDisplayName: Eshaan IITM
Body: <p>I want to do pathway enrichment analysis in python using <code>scipy.stats.hypergeom.sf function</code> to select pathways that are significantly enriched in at least one tissue.</p>
  <p>my data:</p>
  <pre><code>Enrichment  CANCER_TYPE PATHWAY
  11.6    Breast Carcinoma    Cell cycle/DNA replication
  2   Breast Carcinoma    Protein stability and degradation/DNA replication
  2.8 Breast Carcinoma    EGFR signaling/DNA replication
  4   Breast Carcinoma    p53 pathway/DNA replication
  0   Breast Carcinoma    PI3K/MTOR signaling/DNA replication
  1.2 Pancreatic Carcinoma    Mitosis/RTK signaling
  3.3 Pancreatic Carcinoma    EGFR signaling/RTK signaling
  </code></pre>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-04-18T20:41:34.580Z
Comments.Text: what is "Enrichment"? usually this kind of data comes in the form of a list of genes with annotations and some sort of background set of annotations for genes in a genome. At a minimum, we would expect some count of genes/gene annotations, which is necessary to get the numbers to plug into a hypergeometric test. Different tools will count annotations differently, perhaps tell us more about where your data table comes from?
Comments.UserDisplayName: Maximilian Press
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-04-19T03:21:07.297Z
Comments.Text: Could you please add some more detail to your question? Context helps a lot. It's great that you've included input data, but we don't know how that data is generated, or what the 'Enrichment' field means.
Comments.UserDisplayName: gringer
Tags: <python><r><scipy>
Title: How to do enrichment analysis with scipy.stats.hypergeom.sf function
ThreadText: # How to do enrichment analysis with scipy.stats.hypergeom.sf function
  
  (Asked by: username_0 on 2022-04-18)
  
  I want to do pathway enrichment analysis in python using `scipy.stats.hypergeom.sf function` to select pathways that are significantly enriched in at least one tissue.
  
  my data:
  
  ```
  Enrichment  CANCER_TYPE PATHWAY
  11.6    Breast Carcinoma    Cell cycle/DNA replication
  2   Breast Carcinoma    Protein stability and degradation/DNA replication
  2.8 Breast Carcinoma    EGFR signaling/DNA replication
  4   Breast Carcinoma    p53 pathway/DNA replication
  0   Breast Carcinoma    PI3K/MTOR signaling/DNA replication
  1.2 Pancreatic Carcinoma    Mitosis/RTK signaling
  3.3 Pancreatic Carcinoma    EGFR signaling/RTK signaling
  
  ```
  
  **Tags:** python, r, scipy
  
  > **Comments:**
  > **username_1**: what is "Enrichment"? usually this kind of data comes in the form of a list of genes with annotations and some sort of background set of annotations for genes in a genome. At a minimum, we would expect some count of genes/gene annotations, which is necessary to get the numbers to plug into a hypergeometric test. Different tools will count annotations differently, perhaps tell us more about where your data table comes from?  
  > **username_2**: Could you please add some more detail to your question? Context helps a lot. It's great that you've included input data, but we don't know how that data is generated, or what the 'Enrichment' field means.  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_3 on 2024-07-17. Score: 1
  
  I guess it is too late to answer this now, but I think you can use `gseapy`. Its a `python` module for performing enrichment analysis. Just install it with:
  
  > `pip install gseapy`
  
  There is also a tutorial of sorts on `Medium`
  <https://medium.com/omics-diary/how-to-use-gseapy-for-pathway-enrichment-analysis-67a1aab1002d>.
  
  
  ---
  
  