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Tile generation for big data

Project description

Clodius

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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.

Demo

Install the clodius package:

pip install clodius

And use it aggregate a bigWig file:

curl https://raw.githubusercontent.com/hms-dbmi/clodius/develop/test/sample_data/geneAnnotationsExonsUnions.short.bed \
  > /tmp/sample.short.bed
clodius aggregate bedfile /tmp/sample.short.bed

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

More examples are available.

File Types

Development

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

pip install -e ".[dev]"

Test Fixtures (Git LFS)

Test data files in data/ are stored in Git LFS. They are downloaded automatically when you clone the repository with LFS enabled:

git lfs install  # once per machine
git clone <repo>  # LFS files downloaded automatically
# or, in an existing clone:
git lfs pull

Adding a new test fixture

  1. Check if the file type is already tracked — open .gitattributes and look for a matching pattern (e.g. data/*.gz, *.bam). If not, add a new tracking rule:

    git lfs track "data/*.ext"   # adds a line to .gitattributes
    git add .gitattributes
    
  2. Allow the file through .gitignoredata/* is ignored by default. Add a negation line for your file:

    !data/your_new_file.ext
    
  3. Stage and commit as normal:

    git add data/your_new_file.ext
    git commit -m "Add test fixture: your_new_file.ext"
    git push  # LFS objects are uploaded automatically
    

Testing

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

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