Open PinpinSui opened 3 months ago
In Condition 2, a TAD gained is equivalent to the loss of the TAD in Condition 1. To identify such TADs, swap Condition 2 as Condition 1 in the input for DiffDomain. See the example code below.
python diffdomains.py dvsd multiple <hic1> <hic0> <tadlist_of_hic1.bed>
Here, hic1
refers to the .hic
file from Condition 2, while hic0
represents the .hic
file from Condition 1. Additionally, tadlist_of_hic1.bed
denotes the list of TADs identified in Condition 2.
Hi Dechao,
Thank you so much for your response! So for the final list of changed TADs in condition 2, should I integrate gain to other 6 types together? I could not see the gained TAD class in Nature communication paper.
Pinpin
Hey Pinpin
There is no need to integrate gained TADs into the reorganized TADs in DiffDomain. The current formulation of DiffDomain focuses on testing whether TADs from condition 1 are reorganized in condition 2, and then classifies the resulting reorganized TADs into 6 subtypes.
In cases where there are gained TADs in condition 2, we can treat condition 2 as the new condition 1 in the input of DiffDomain. This approach allows us to classify the gained TADs in condition 2 as lost TADs in condition 1, without needing to integrate them into the reorganized TADs.
Dechao
Hi Dechao,
Appeciate your explanation! Thank you again for this wonderful diffdomain!
Pinpin
Hi Dechao,
Thank you again! Another question, how to distinguish the strength change up and strength change down TADs with diffdomain?
Pinpin Sui
Hi,
Thanks for this wonderful tool to see the TAD changes among 2 condition! How to identity the gained loops in condition 2?
Thank you, Pinpin Sui