semvec/pypi-packages huggingface dataset:
iceDP 1.0.0
Identify inter-chromatin interaction utilize density peaks algorithm
License: MIT


## iceDP project description


### Installation
Way one
```shell
copy to ${python_path}/site-packages
```

Way two
```shell
    pip install iceDP  # not up load yet
```


### Usage
* Data required

iceDP receive any genome interaction data in a three-column format as input. Before running analyses, we need to prepare genome interaction data in a three-column format:

    Column 1 (chr_one_site) → Genomic position on the first chromosome.

    Column 2 (chr_two_site) → Genomic position on the second chromosome.

    Column 3 (interaction_value) → Interaction strength between the two positions (typically observed in Hi-C experiments).

Check the sample data:
```shell
head -5 play_data/chr4_chr11_mm10.txt
3090000 3100000 1.0
3795000 3100000 1.0
4205000 3100000 1.0
4255000 3100000 1.0
4230000 3105000 1.0
```
This file represents genomic interactions between chromosome 4 and chromosome 11 in the mouse genome (mm10).


If your data is stored in .hic format, you can extract interaction values using Juicer Tools:

```shell
java -jar juicer_tools.jar dump observed NONE mydata.hic chr4 chr11 BP 50000 chr4_chr11_mm10.txt
```

Juicer Tools can be fetch from:
https://github.com/aidenlab/juicertools



* iceDP procedure
```python
    import iceDP

    x=iceDP.main_procedure.bunchDots()
    x.readData('play_data/chr4_chr11_mm10.txt')
    x.get_rho()    # calculate rho
    x.get_delta()  # calculate delta
    x.do_chi_square_test()
    x.define_border()
    x.horizontal_and_vertical_fold_change()
    iceDP.main_procedure.save_reult(x, 'chr4_chr11_mm10_DPresult')  # save result
```

* plot
```python
    iceDP.plot_spots.plot_one_spot(x.data_filted2.values[1], x)
```