Dummy change to see if travis would fail , because of pysam-developers/pysam#860 (comment)
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.
- Non-genomic Rasters
- Genomic Data
The recommended way to develop clodius
is to use a conda environment and
install clodius
with develop mode:
pip install -e .
The unit tests for clodius can be run using pytest:
pytest
Individual unit tests can be specified by indicating the file and function they are defined in:
pytest test/cli_test.py:test_clodius_aggregate_bedgraph
If you don't have your own, get some sample data:
mkdir -p /tmp/clodius/input
mkdir -p /tmp/clodius/output
curl https://raw.githubusercontent.com/hms-dbmi/clodius/develop/test/sample_data/geneAnnotationsExonsUnions.short.bed \
> /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.