Docker image of CustardPy, the Hi-C analysis pipeline.
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To use the docker command, type:
# Pull docker image
docker pull rnakato/custardpy
# Container login
docker run --rm -it rnakato/custardpy /bin/bash
# Execute a command
docker run --rm -it -v (your directory):/opt/work rnakato/custardpy <command>
When calling loops using Juicer HICCUPS, supply the --gpus all option to allow GPU computation (GPU card needed):
docker run --gpus all -it --rm -it -v (your directory):/opt/work rnakato/custardpy call_HiCCUPS.sh
Singularity is the alternative way to use CustardPy. With this command you can build the singularity file (.sif) of CustardPy:
singularity build custardpy.sif docker://rnakato/custardpy
Instead, you can download the CustardPy singularity image from our Dropbox (We use singularity version 3.8.5).
Then you can run CustardPy with the command:
singularity exec custardpy.sif <command>
Singularity will automatically mount the current directory. If you want to access the files in the other directory, use the --bind option, for instance:
singularity exec --bind /work custardpy.sif <command>
This command mounts the /work directory.
When calling loops using Juicer HICCUPS, supply --nv option to allow GPU computation (GPU card needed):
singularity exec --bind /work custardpy.sif call_HiCCUPS.sh
# download Churros/tutorial directory
git clone https://github.com/rnakato/CustardPy.git
cd CustardPy/tutorial/Hi-C/
# download fastq and genome data and make index
bash 00_getdata.sh
# Execute Juicer pipeline
bash QuickStart_juicer.sh
See https://custardpy.readthedocs.io for the detailed Manual.
First clone and move to the repository
git clone https://github.com/rnakato/CustardPy.git
cd CustardPy/Docker
Then type:
docker build -f Dokerfile.<version> -t <account>/custardpy_juicer .
Content type
Image
Digest
sha256:dcecd3231…
Size
25 GB
Last updated
3 months ago
docker pull rnakato/custardpy