Question: Interpretation of Beta values : Methylation data
gravatar for Tanvir Ahamed
2.9 years ago by
Tanvir Ahamed 270 wrote:

Beta values (β) are the estimate of methylation level using the ratio of intensities between methylated and unmethylated alleles. β are between 0 and 1 with 0 being unmethylated and 1 fully methylated.

Now when compare values of a probe form 2 different sample, how to compare if methylated or unmethylated . As for example,

probe  sample_A  Sample_B
cg_1      0.6       0.7
cg_2      0.2       0.3
cg_3      0.8       0.9
cg_4      0.2       0.9
cg_5      0.3       0.6
cg_6      0.1       0.4

Now how to compare a specific probe if methylated or not.

Some assumption :

  1. If a specific value ( 0.5) define methylated (greater than 0.5) or unmethylated (less than 0.5) state.
  2. If it is reasonable to measure the change ( difference) of beta values. For cg_6 difference is 0.3 (0.4-0.1), though the maximum value is less than 0.5.
  3. Or if consider both situation together.

May be the issue is really simple. But i am a bit unclear regarding this issue. I am expecting some expert's thinking on this issue.

Partly related : Interpreting Fractional Methylation Data


methylation • 7.7k views
ADD COMMENTlink modified 2.9 years ago • written 2.9 years ago by Tanvir Ahamed 270
gravatar for Devon Ryan
2.9 years ago by
Devon Ryan88k
Freiburg, Germany
Devon Ryan88k wrote:
  1. This assumption is incorrect. A position is only ever has a binary methylated/unmethylated state on a single copy of a chromosome in a single cell. A value of 0.5 typically indicates that the underlying cells that were sampled are highly variable (it's the unclear whether there are multiple 0% and 100% methylation populations or if there's a more heterogeneous mix).
  2. Yes, this is reasonable, though in reality there's noise around the estimate of 0.1 and 0.4 and this should be taken into consideration.
  3. This will depend completely on what you want to do.

There are already a number of Bioconductor packages for handling methylation data. I would strongly encourage you to use one of them and not try to come up with your own methods.

ADD COMMENTlink written 2.9 years ago by Devon Ryan88k

Thanks for your thought. Can you suggest some function/package those handle this type of situation ?

ADD REPLYlink written 2.9 years ago by Tanvir Ahamed 270

It depends on the exact question and the dataset. In general, just look through the Bioconductor DNAMethylation view and you'll be able to narrow down the options to a couple possibilities.

ADD REPLYlink written 2.9 years ago by Devon Ryan88k

Dear Devon,

In this case (1), is it OK to consider that a value of 0.1 would indicate that 10% of my samples were methylated, while the rest were not?

Thanks in advance

ADD REPLYlink written 6 weeks ago by vinayjrao110
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