1. Installation

1.1. CustardPy Docker image

Note

From version 1, the CustardPy docker image supports all analyses previously offered by CustardPy and CustardPy_Juicer images, rendering the latter unnecessary.

Docker image of CustardPy is available at DockerHub. This image contains various tools for Hi-C/Micro-C analysis in addition to CustardPy core components as below:

For a full description of each tool, visit the original website.

1.1.1. RUN

For Docker:

# pull docker image
docker pull rnakato/custardpy

# container login
docker run [--gpus all] --rm -it rnakato/custardpy /bin/bash

# execute a command
docker run [--gpus all] --rm -it rnakato/custardpy <command>

For Singularity:

# build image
singularity build custardpy.sif docker://rnakato/custardpy

# execute a command
singularity exec [--nv] custardpy.sif <command>

Note

--gpus all for Docker and --nv option for Singularity allow using GPU. This option is needed only when calling loops by HiCCUPS.

1.2. CustardPy from PyPI

Core components of CustardPy (e.g., commands for visualization) can by installed using pip (>= Python 3.7):

pip3 install custardpy