TAD-Lactuca is a tool to predict Topologically Associating Domains(TAD) boundary using histone marks information. It was written in Python language, using Random Forests(RF) and Multilayer Perception(MLP).
- The
data
fold contains the origin data (expect the bigwig file, the detail can be found in paper) - The
src
fold contains all scripts, such as data processing, modeling and plot. - The
cache
fold contains the main result and some processed the multiple resolution feature signal, such as thebin's
length range(40kb,20kb,10kb
), thebin's
number range(10,8,6). - The
pic
fold contains the all signal pattern of different feature.
- Python3.*
- Numpy
- Pandas
- Tensorflow / Tensorflow-gpu
- Keras
- Scikit-Learn
- Matplotlib
The data
fold contains the original files, the signals of different type histone were calculate by bedtool
, the details can be seen from ./src/utils/get_signal_plot.py
If you want to use the example data, you can run the script as:
python3 tad_lactuca.py
If you want to use your own data, please run the script as:
python3 tad_lactuca.py [the path of your data]
- The feature data of the locus you want to know is boundary or not
- Only the base location you want to know is in the domain or boundary
- The probability of the input data belong to each category.
- The signal of the locus.