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vaquerizaslab / fanc

FAN-C: Framework for the ANalysis of C-like data
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How should I understand aggregate in fanc using detected Hi-C TAD regions ? #119

Open JungWoongJae opened 2 years ago

JungWoongJae commented 2 years ago

Hi, I’m using fanc to analysis some kind of HiC data.

First, thank you for the great effort and job making such a nice tool.

While using it, I approached to some queusions in aggregate command.

  1. If I have used TAD regions as input for the FAN-C aggregate, can I understand the results that they are showing the strength of each TADs?

  2. If the answer to question number 1 is yes, can I say for example let's assume that the control and the other sample have the same TAD region. If the control TAD strength is 0.5 and the other sample's TAD strength is 1, can I say that the other sample's intra TAD interaction strength is stronger?

  3. If the answer to question number 1 is no, then how should I understand the output value for the FAN-C aggregate method?

  4. I tried to find how they are calculated, but failed. Could you give me some advise in how is the value of returned text file is calculated in fanc aggregate method?

For example,

what you have mentioned in the aggregate related document, it says

“It can be very informative to view the average Hi-C matrix for a set of regions, rather than the Hi-C matrix at each individual region“

In this point of view, I’m willing to know interaction values at each individual region(not a loop, broad region like TAD) to compare with other samples, not the average Hi-C matrix for a set of regions.

I simply thought the result values returned by fanc aggregate method as the intra TAD interaction strength, but when I looked into specific TAD which have up regulated interactions in treated sample, the value I got was lower than control sample.

It would be very grateful if you could give me some guidance for how could I get such individual interaction strength in each TADs or how should I understand the meaning of values in each TADs in a text file returned from aggregate method.

Thanks a lot!

kaukrise commented 2 years ago

Hey, I am currently on holiday, so I won't have time to reply in detail, but FAN-C uses the methodology presented here:

https://www.nature.com/articles/nature21711

I advise reading that publication first, and if there are still questions I can answer them when I get back

JungWoongJae commented 2 years ago

Hey, I am currently on holiday, so I won't have time to reply in detail, but FAN-C uses the methodology presented here:

https://www.nature.com/articles/nature21711

I advise reading that publication first, and if there are still questions I can answer them when I get back

Thank you for the reply even in holiday! I’ll look into the paper and tell you if I still have problem understanding it.

Thanks again for the great job and the reply. Have a nice holiday :)