add XGBoost to list of available methods #189
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| on: | |
| push: | |
| branches: | |
| - main | |
| paths: | |
| - 'flexynesis/**' | |
| - '.github/workflows/**' | |
| - './spec-file.txt' | |
| - './pyproject.toml' | |
| - './manifest.scm' | |
| - './guix.scm' | |
| jobs: | |
| run_package: | |
| runs-on: ubuntu-latest | |
| steps: | |
| - name: Checkout repository | |
| uses: actions/checkout@v2 | |
| - name: Set up Python | |
| uses: actions/setup-python@v2 | |
| with: | |
| python-version: '3.11' | |
| - name: Set up Miniconda | |
| uses: conda-incubator/setup-miniconda@v2 | |
| with: | |
| auto-update-conda: true | |
| python-version: '3.11' | |
| - name: Cache Conda environment | |
| uses: actions/cache@v2 | |
| with: | |
| path: ~/miniconda/envs | |
| key: ${{ runner.os }}-conda-${{ hashFiles('spec-file.txt') }} | |
| restore-keys: | | |
| ${{ runner.os }}-conda- | |
| - name: Create environment with dependencies | |
| shell: bash -l {0} | |
| run: | | |
| conda create --name my_env --file spec-file.txt | |
| conda activate my_env | |
| - name: Install my package from source | |
| shell: bash -l {0} | |
| run: | | |
| conda activate my_env | |
| pip install -e . | |
| - name: Download dataset1 | |
| run: | | |
| curl -L -o dataset1.tgz https://bimsbstatic.mdc-berlin.de/akalin/buyar/flexynesis-benchmark-datasets/dataset1.tgz | |
| tar -xzvf dataset1.tgz | |
| - name: Download stringdb data | |
| run: | | |
| wget https://stringdb-downloads.org/download/protein.links.v12.0/9606.protein.links.v12.0.txt.gz | |
| gzip -cd 9606.protein.links.v12.0.txt.gz > dataset1/9606.protein.links.v12.0.txt | |
| wget https://stringdb-downloads.org/download/protein.aliases.v12.0/9606.protein.aliases.v12.0.txt.gz | |
| gzip -cd 9606.protein.aliases.v12.0.txt.gz > dataset1/9606.protein.aliases.v12.0.txt | |
| - name: Download dataset2 | |
| run: | | |
| curl -L -o dataset2.tgz https://bimsbstatic.mdc-berlin.de/akalin/buyar/flexynesis-benchmark-datasets/dataset2.tgz | |
| tar -xzvf dataset2.tgz | |
| - name: Download LGG_GBM_dataset | |
| run: | | |
| curl -L -o lgggbm_tcga_pub_processed.tgz https://bimsbstatic.mdc-berlin.de/akalin/buyar/flexynesis-benchmark-datasets/lgggbm_tcga_pub_processed.tgz | |
| tar -xzvf lgggbm_tcga_pub_processed.tgz | |
| - name: Run DirectPred | |
| shell: bash -l {0} | |
| run: | | |
| conda activate my_env | |
| flexynesis --data_path dataset1 --model_class DirectPred --target_variables Erlotinib --fusion_type early --hpo_iter 1 --features_min 50 --features_top_percentile 5 --log_transform False --data_types gex,cnv --outdir . --prefix erlotinib_direct --early_stop_patience 3 --use_loss_weighting False | |
| - name: Run DirectPred_TestSurvival | |
| shell: bash -l {0} | |
| run: | | |
| conda activate my_env | |
| flexynesis --data_path lgggbm_tcga_pub_processed --model_class DirectPred --target_variables STUDY --fusion_type intermediate --hpo_iter 1 --features_min 50 --features_top_percentile 5 --log_transform False --data_types mut,cna --outdir . --prefix lgg_surv --early_stop_patience 3 --use_loss_weighting False --surv_event_var OS_STATUS --surv_time_var OS_MONTHS | |
| - name: Run supervised_vae | |
| shell: bash -l {0} | |
| run: | | |
| conda activate my_env | |
| flexynesis --data_path dataset1 --model_class supervised_vae --target_variables Erlotinib,Crizotinib --fusion_type early --hpo_iter 1 --features_min 50 --features_top_percentile 5 --log_transform False --data_types gex,cnv --outdir . --prefix erlotinib_svae --early_stop_patience 3 --use_loss_weighting True | |
| - name: Run CrossModalPred | |
| shell: bash -l {0} | |
| run: | | |
| conda activate my_env | |
| flexynesis --data_path dataset1 --model_class CrossModalPred --target_variables Erlotinib --fusion_type intermediate --hpo_iter 1 --features_min 50 --features_top_percentile 5 --log_transform False --data_types gex,cnv --input_layers gex --output_layers cnv --outdir . --prefix erlotinib_crossmodal --early_stop_patience 3 --use_loss_weighting True | |
| - name: Run MultiTripletNetwork | |
| shell: bash -l {0} | |
| run: | | |
| conda activate my_env | |
| flexynesis --data_path dataset2 --model_class MultiTripletNetwork --target_variables y --fusion_type early --hpo_iter 1 --features_min 50 --features_top_percentile 5 --log_transform False --data_types gex,meth --outdir . --prefix msi_triplet --early_stop_patience 3 | |
| - name: Run GNN | |
| shell: bash -l {0} | |
| run: | | |
| conda activate my_env | |
| flexynesis --data_path dataset1 --model_class GNN --target_variables Erlotinib --fusion_type intermediate --hpo_iter 1 --features_top_percentile 10 --log_transform False --data_types gex --outdir . --prefix erlotinib_direct --early_stop_patience 3 --use_loss_weighting False --subsample 50 |