clarification about bumphunter value output
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src3 • 0
@src3-15184
Last seen 6.1 years ago

How can the values in value column of the bumphunter output be greater than 1 or less than 0 if beta values range from 0 to 1? Is there a log transformation taking place at some point? 

Thank you!

minfi bumphunter • 3.0k views
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Hey! How did you manage to get the beta values then?

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Chloroform is a type of chemical which is used as a Bioconductor. If you are a write paper for me chemistry student, then you will be aware of it. Its composition is composed of alcohol and anesthesia. It is made of these components. It is used to give people a temporary sign of sleep.

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Thanks for sharing this post

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@james-w-macdonald-5106
Last seen 10 hours ago
United States

Ideally you would be using M-values rather than beta values, as they are more amenable to analysis using tools like lmFit. In which case they range from -Inf to Inf (hypothetically), and it wouldn't be surprising at all to have a beta larger than 1 or less than zero.

But your question has more to do with how bumphunter works in a statistical sense, which is ideally something you would understand before using the software. You would be well served to read the bumphunter vignette as well as the papers that describe the method.

 

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Yuan Tian ▴ 270
@yuan-tian-13904
Last seen 2.5 years ago
United Kingdom

Hello:

I remember bumphunter use coefficient or t-statistic to calculate DMRs, not beta value. Thus the value you can see in the output is not beta value I think, it's a smoothed coef. 

And you are right that seems it's pretty hard to find clear explanations for bumphunter output. When I code ChAMP, I basically read every line of bumphunter to understand how it works (because users ask me via email, I am maintaining ChAMP), below is my explanation:

1)      value:  Mean value of all smooth coef in one candidate bump.

2)      L: Numbers of CpGs contained in candidate bump.

3)      p.value:  Proportion of random bumps show most CpGs and higher mean value then this DMR.

4)      fwer:  Proportion that a random run would generate one such DMR shows most CpGs and higher mean value.

5)      p.valueArea:  Proportion of random bumps show higher abs sum value then this DMR.

6)      fwerArea: Proportion that a random run would generate one such DMR show higher abs sum value.

Best

Yuan Tian

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Is there a way to get beta values from these values?

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Is there a way to get beta values from these values?

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No, these are all values available. Beta value needs to be extracted yourself from origin beta matrix.

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How can I know which DMR is hypomethylated using bumphunter, since there is no specific statement in the document which phenotype is used as reference?

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