Metadata-Version: 2.1
Name: custardpy
Version: 0.0.2
Summary: Hi-C analysis tools by Python3
Home-page: https://github.com/rnakato/custardpy
Author: Ryuichiro Nakato
Author-email: rnakato@iqb.u-tokyo.ac.jp
License: GPL3.0
Keywords: Hi-C analysis,3D genome,NGS
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: numpy (>=1.18)
Requires-Dist: pandas (>=1.3.0)
Requires-Dist: scipy (>=1.3)
Requires-Dist: scikit-learn (>=1.0.0)
Requires-Dist: matplotlib (>=3.2.2)
Requires-Dist: seaborn (>=0.11.1)
Requires-Dist: h1d (>=0.2.0)
Requires-Dist: hic-straw (>=1.3.0)

# CustardPy

Hi-C analysis tools by Python3 and Docker


## Requirements

The following are required before installing CustardPy:

- Python 3.7+

## Installation

### From PyPI

Core components of CustardPy can by installed using pip:

    pip3 install custardpy

### Docker image

We recommend to use the [CustardPy Docker image](https://hub.docker.com/r/rnakato/custardpy) that contains additional scripts for Hi-C/Micro-C analysis.

#### Docker 
To use docker command, type:

    docker pull rnakato/custardpy
    docker run -it --rm rnakato/custardpy <command>

#### Singularity

Singularity can also be used to execute the docker image:

    singularity build custardpy.sif docker://rnakato/custardpy
    singularity exec custardpy.sif <command>

Singularity mounts the current directory automatically. If you access the files in the other directory, please mount by `--bind` option, for instance:

    singularity exec --bind /work custardpy.sif <command>
    
This command mounts `/work` directory.

## Usage

See https://custardpy.readthedocs.io for the detailed Manual.

## Reference

- Nakato R, Sakata T, Wang J, Nagai LAE, Oba GM, Bando M, Shirahige K, Context-dependent 3D genome regulation by cohesin and related factors, bioRxiv, 2022. doi: [10.1101/2022.05.24.493188](https://www.biorxiv.org/content/10.1101/2022.05.24.493188v1)
