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Clodius is a tool for breaking up large data sets into smaller tiles that can subsequently be displayed using an appropriate viewer.
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Displaying large amounts of data often requires first turning it into not-so-large amounts of data. Clodius is a program and library designed to aggregate large datasets to make them easy to display at different resolutions.


Install the clodius package:

pip install clodius

And use it aggregate a bigWig file:

clodius aggregate bigwig ~/Downloads/E116-DNase.fc.signal.bigwig

The output files can then be displayed using the higlass-docker container. For more information about viewing these types of files take a look at the higlass wiki.

More examples are available.

File Types


The recommended way to develop clodius is to use a conda environment and install clodius with develop mode:

python develop

Note that making changes to the clodius/fast.pyx cython module requires an explicit recompile step:

python build_ext --inplace


The unit tests for clodius can be run using nosetests:

nosetests test

Individual unit tests can be specified by indicating the file and function they are defined in:

nosetests test/

Quick start with Docker

If you don't have your own, get some sample data:

mkdir -p /tmp/clodius/input
mkdir -p /tmp/clodius/output
curl \
  > /tmp/clodius/input/sample.short.bed

Then install Docker, and pull and run the Clodius image:

docker stop clodius;
docker rm clodius;

docker pull gehlenborglab/clodius # Ensure that you have the latest.

docker run -v /tmp/clodius/:/tmp/ \
           gehlenborglab/clodius \
           clodius aggregate bigwig /tmp/input/file.bigwig

ls /tmp/clodius/output # Should contain the output file

If you already have a good location for your input and output files, reference that in the -v arguments above, instead of /tmp/clodius. The other scripts referenced below can be wrapped similarly.

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