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This repository was created to prototype the DVC-based ML pipelines for the crosspecies project All dependencies are written in conda environment.yaml file, DVC and jupyter lab are also installed there.
In the data folder one keeps input, interim and output data.
Before you start running anything do not forget to dvc pull the data and after commiting do not forget to dvc push it!
The pipeline is run by running dvc stages (see stages folder)
Most of the analysis is written in jupyter notebooks in the notebooks folder. Each stage runs (and source controls input-outputs) corresponding notebooks using papermill software (which also stores output of the notebooks to data/notebooks)
Temporaly some classes are copy-pasted from xspecies repository to make notebooks works
The code in yspecies folder is a conda package that is used inside notebooks
DVC stages are inside stages folder (together with yaml files in parameters). To run dvc stage just use dvc repro command, like:
dvc repro -f stages/1_select_genes_and_species.dvc
Most of the stages also produce notebooks together with files in the output
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