What statistical test should I apply to prove my high confidence values are part of low confidence values?

Question

[morovatunc]

Dear all,

I got chip seq peak results with bed format. There are 7 normal vs 13 tumor samples. I have two consensus peak results from this data.

1. I calculated overlap regions of normal and tumor samples separately first. After that, I compared two groups. This is my high confidence peaks.
2. I piped merged all normal files and tumor files into separate bed then, calculated the overlaps. This is my low confidence peaks.

I wanted to show that 1st one is part of my 2nd group statistically. I decided to apply t test but I couldn't figure out a way to implement it to bed files. Could you show me way to do that?

Thank you for your help.

Best regards,
Tunc

Answer 1

[yupeng he]

It does not look like that a statistical test is needed here. If I understand correctly, all of your high confidence peak will be in the low confidence peak. There is no randomness here.

Why do you want to test the overlap? Is there any randomness (e.g. random error or variation due to sampling) you are worrying about?

[morovatunc]

actually there is not any randomness. I just want to explain the relationship with low vs high confidences. For example, some percent of my low confidence values is also shown in high confidence etc.. My question might be very stupid therefore I apologise if I ask something too basic or stupid.

[yupeng he]

No worries. I was trying to understand. Reporting the percentages should be ok. For example, the fraction of low confidence peaks is high confidence peaks.

[yupeng he]

If there is no randomness, a test is not needed. Description should be good enough. If you are curious about the case with randomness, you may want to look into proportion test:

http://stattrek.com/hypothesis-test/proportion.aspx?Tutorial=AP

[morovatunc]

Thank you for your help ! I will read this topic and learn more about the concepts.

Answer 2

[andrew.j.skelton73]

Hi, did you see this post a couple of days ago? May be useful for your problem!