Answers.Body: <p>Methylation levels have high local correlation, so Fisher's method would be problematic. Having said that, you have no reason to use Fisher's method after a paired t-test. A paired t-test will give you a single p-value per gene, which is what you want. Do be sure to only include CpG with some minimal coverage in both group.</p>
  
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Answers.CreationDate: 2017-08-10T18:11:16.970Z
Answers.LastActivityDate: 2017-08-10T18:11:16.970Z
Answers.UserDisplayName: Devon Ryan
Answers.Body: <p>What is typically done in methylation analysis is to assess the islands of methylations. </p>
  
  <p>Check <a href="https://www.bioconductor.org/help/workflows/methylationArrayAnalysis/#customising-visualisations-of-methylation-data" rel="nofollow noreferrer">this workflow</a>, in the section linked it uses some predefined islands for instance. I am no expert on this area but you could asses if the islands or certain regions are more methylated than expected.</p>
  
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Answers.CreationDate: 2017-09-12T09:13:45.453Z
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Answers.UserDisplayName: llrs
Body: <p>I have some data I am working with, and I am curious if I am able to combine p-values from a paired t-test for CpG sites in the genome using Fisher's Method to get one p-value for each unique gene. Linked <a href="https://en.wikipedia.org/wiki/Fisher%27s_method" rel="noreferrer">here</a> is the Wikipedia page for Fisher's Method. I understand that an assumption of the method used is that each individual p-value being combined must be independent. I'm relatively new to biostatistics, so I'm curious if using CpGs from the same gene would violate this assumption.</p>
  
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2017-08-11T10:54:03.857Z
Comments.Text: Why do you want to melt CpG values? Do you want to know if an specific gene/region is more phosphorylated than others? What are your hypothesis (you tell about a t-test for the CpG sites? Are you testing if they are phosphorylated vs not or more than the rest of the genome or...?
Comments.UserDisplayName: llrs
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Comments.CreationDate: 2017-09-12T10:05:45.413Z
Comments.Text: In a nutshell, your intuition is correct: they are not independent.
Comments.UserDisplayName: Konrad Rudolph
Tags: <r><bioconductor><gene><methylation>
Title: Melt p-values for CpG sites mapping to the same gene
ThreadText: # Melt p-values for CpG sites mapping to the same gene
  
  (Asked by: username_0 on 2017-08-10)
  
  I have some data I am working with, and I am curious if I am able to combine p-values from a paired t-test for CpG sites in the genome using Fisher's Method to get one p-value for each unique gene. Linked [here](https://en.wikipedia.org/wiki/Fisher%27s_method) is the Wikipedia page for Fisher's Method. I understand that an assumption of the method used is that each individual p-value being combined must be independent. I'm relatively new to biostatistics, so I'm curious if using CpGs from the same gene would violate this assumption.
  
  **Tags:** r, bioconductor, gene, methylation
  
  > **Comments:**
  > **username_1**: Why do you want to melt CpG values? Do you want to know if an specific gene/region is more phosphorylated than others? What are your hypothesis (you tell about a t-test for the CpG sites? Are you testing if they are phosphorylated vs not or more than the rest of the genome or...?  
  > **username_2**: In a nutshell, your intuition is correct: they are not independent.  
  
  ---
  
  ## 2 answers
  
  ### Answer by username_3 on 2017-08-10. Score: 6
  
  Methylation levels have high local correlation, so Fisher's method would be problematic. Having said that, you have no reason to use Fisher's method after a paired t-test. A paired t-test will give you a single p-value per gene, which is what you want. Do be sure to only include CpG with some minimal coverage in both group.
  
  
  ---
  
  ### Answer by username_1 on 2017-09-12. Score: 1
  
  What is typically done in methylation analysis is to assess the islands of methylations.
  
  Check [this workflow](https://www.bioconductor.org/help/workflows/methylationArrayAnalysis/#customising-visualisations-of-methylation-data), in the section linked it uses some predefined islands for instance. I am no expert on this area but you could asses if the islands or certain regions are more methylated than expected.
  
  
  ---
  
  