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Major data model refactor #177
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# Conflicts: # requirements.txt
- removed obsolete build_Dataset_yaml to avoid confusion - datasets are always called datasetname.yaml (avoid 'dataset_dataset.yaml' since it's confusing) - in build_dataset_overview_yaml: remove option to have datasets with multiple names, it is always called 'dataset' - central dataset discovery in Galaxy Util - renamed ambiguous name build_yaml_from_arguments to build_train_ml_model_yaml.py - training split size for clustering instruction
- Made some tests faster by using smaller dummy datasets
- discover dataset type from dataset.yaml file if provided
- add explicit parameter 'label_columns' to import params -> imports only those labels if specified (avoids clutter on galaxy) - update importer docs
…unt = 2, does the following: - if count >2, the top chain pair is selected based on duplicate_count. if duplicate_count is not available, they are selected randomly - if count <2, receptor is removed. this removal now also includes receptors with 2 identical chains (e.g.,TRB+TRB)
…sed on umi count, then duplicate count)
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Major updates: