4DMax is a tool for prediction of the 4dgenome conformation from a time-series Hi-C dataset
4DMax runs entirely in python. Use expects access to a GPU. To install use 'conda env create -f environment.yml'
1. Format your time series Hi-C data
Each Hi-C experiment should be represented as a 3 column tab seperated text file where (pos1, pos2, val)
2. Build dataset and hyper parameters configuration files
examples shown in:
-
Config/Datasets/example.json
-
Config/Hyper_Params/example.json
Hyper Params
- eta: weight of movement loss
- alpha: contact map to distance constraint conversion ratio IF=d^alpha
- lr: learning rate
- epoch: number of epochs to train
Data Set
- name: genomic Process name
- step: granularity of 4D Model
- chro: chromosome number
- rep: biological replicate number
- taos: indx of hi-c experiments in time process
- datasets: hi-c experiment text files
3. Run 4DMax 'python 4dmax.py {input.dataset} {input.param}'
4 View Strucutes 'python Python_Scripts/create_gif.py {output.outfig} {input.npfile}
- Download needed Hi-C files Cardiomyocyte GSE106690 iPSC GSE96611
- Generate modes 'snakemake'
- Generate TADS 'cd TADS; snakemake --use-conda '
- Generate AB Compartments: 'cd AB; snakemake'