Question: clarification about bumphunter value output
0
gravatar for src3
18 months ago by
src30
src30 wrote:

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 • 393 views
ADD COMMENTlink modified 18 months ago by Yuan Tian110 • written 18 months ago by src30

Hey! How did you manage to get the beta values then?

ADD REPLYlink written 5 months ago by mhebba0
Answer: clarification about bumphunter value output
0
gravatar for James W. MacDonald
18 months ago by
United States
James W. MacDonald51k wrote:

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.

 

ADD COMMENTlink written 18 months ago by James W. MacDonald51k
Answer: clarification about bumphunter value output
0
gravatar for Yuan Tian
18 months ago by
Yuan Tian110
University College London
Yuan Tian110 wrote:

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

ADD COMMENTlink written 18 months ago by Yuan Tian110

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

ADD REPLYlink written 5 months ago by mhebba0

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

ADD REPLYlink written 5 months ago by mhebba0

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

ADD REPLYlink written 5 months ago by Yuan Tian110
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