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📝 update READMEs and add some hints to config files
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| # Alzheimer study configuration | ||
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| For [`workflow/Snakefile_v2.yaml`](https://github.com/RasmussenLab/pimms/blob/HEAD/project/workflow/Snakefile_v2.smk): | ||
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| - [`config.yaml`](config.yaml) | ||
| - see comments in config for explanations. | ||
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| For [`workflow/Snakefile_ald_comparison](https://github.com/RasmussenLab/pimms/blob/HEAD/project/workflow/Snakefile_ald_comparison.smk): | ||
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| - [`comparison.yaml`](comparison.yaml) |
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| # config for Snakefile_v2.smk | ||
| config_split: runs/alzheimer_study/split.yaml # ! will be build | ||
| config_train: runs/alzheimer_study/train_{model}.yaml # ! will be build | ||
| folder_experiment: runs/alzheimer_study | ||
| fn_rawfile_metadata: https://raw.githubusercontent.com/RasmussenLab/njab/HEAD/docs/tutorial/data/alzheimer/meta.csv | ||
| cuda: False | ||
| file_format: csv | ||
| split_data: | ||
| FN_INTENSITIES: https://raw.githubusercontent.com/RasmussenLab/njab/HEAD/docs/tutorial/data/alzheimer/proteome.csv | ||
| sample_completeness: 0.5 | ||
| feat_prevalence: 0.25 | ||
| column_names: | ||
| - protein groups | ||
| index_col: 0 | ||
| meta_cat_col: _collection site | ||
| meta_date_col: null | ||
| frac_mnar: 0.25 | ||
| frac_non_train: 0.1 | ||
| config_split: runs/alzheimer_study/split.yaml # ! will be build by workflow | ||
| config_train: runs/alzheimer_study/train_{model}.yaml # ! will be build by workflow | ||
| folder_experiment: runs/alzheimer_study # folder to save the results | ||
| fn_rawfile_metadata: https://raw.githubusercontent.com/RasmussenLab/njab/HEAD/docs/tutorial/data/alzheimer/meta.csv # metadata file | ||
| cuda: False # use GPU? | ||
| file_format: csv # intermediate file formats | ||
| split_data: # for 01_01_split_data.ipynb -> check parameters | ||
| FN_INTENSITIES: https://raw.githubusercontent.com/RasmussenLab/njab/HEAD/docs/tutorial/data/alzheimer/proteome.csv | ||
| sample_completeness: 0.5 | ||
| feat_prevalence: 0.25 | ||
| column_names: | ||
| - protein groups | ||
| index_col: 0 | ||
| meta_cat_col: _collection site | ||
| meta_date_col: null # null if no date column, translated to None in Python | ||
| frac_mnar: 0.25 | ||
| frac_non_train: 0.1 | ||
| models: | ||
| - Median: | ||
| model: Median | ||
| - CF: | ||
| model: CF | ||
| latent_dim: 50 | ||
| batch_size: 1024 | ||
| epochs_max: 100 | ||
| sample_idx_position: 0 | ||
| cuda: False | ||
| save_pred_real_na: True | ||
| - DAE: | ||
| model: DAE | ||
| latent_dim: 10 | ||
| batch_size: 64 | ||
| epochs_max: 300 | ||
| hidden_layers: "64" | ||
| sample_idx_position: 0 | ||
| cuda: False | ||
| save_pred_real_na: True | ||
| - VAE: | ||
| model: VAE | ||
| latent_dim: 10 | ||
| batch_size: 64 | ||
| epochs_max: 300 | ||
| hidden_layers: "64" | ||
| sample_idx_position: 0 | ||
| cuda: False | ||
| save_pred_real_na: True | ||
| - KNN: | ||
| model: KNN | ||
| neighbors: 3 | ||
| file_format: csv | ||
| - Median: # name used for model with this configuration | ||
| model: Median # model used | ||
| - CF: | ||
| model: CF # notebook: 01_1_train_{model}.ipynb will be 01_1_train_CF.ipynb | ||
| latent_dim: 50 | ||
| batch_size: 1024 | ||
| epochs_max: 100 | ||
| sample_idx_position: 0 | ||
| cuda: False | ||
| save_pred_real_na: True | ||
| - DAE: | ||
| model: DAE | ||
| latent_dim: 10 | ||
| batch_size: 64 | ||
| epochs_max: 300 | ||
| hidden_layers: "64" | ||
| sample_idx_position: 0 | ||
| cuda: False | ||
| save_pred_real_na: True | ||
| - VAE: | ||
| model: VAE | ||
| latent_dim: 10 | ||
| batch_size: 64 | ||
| epochs_max: 300 | ||
| hidden_layers: "64" | ||
| sample_idx_position: 0 | ||
| cuda: False | ||
| save_pred_real_na: True | ||
| - KNN: | ||
| model: KNN | ||
| neighbors: 3 | ||
| file_format: csv | ||
| - KNN5: | ||
| model: KNN | ||
| neighbors: 5 | ||
| file_format: csv | ||
| NAGuideR_methods: | ||
| - BPCA | ||
| - COLMEDIAN | ||
| - IMPSEQ | ||
| - IMPSEQROB | ||
| - IRM | ||
| - KNN_IMPUTE | ||
| - LLS | ||
| # - MICE-CART > 1h20min on GitHub small runner | ||
| # - MICE-NORM ~ 1h on GitHub small runner | ||
| - MINDET | ||
| - MINIMUM | ||
| - MINPROB | ||
| - MLE | ||
| - MSIMPUTE | ||
| - MSIMPUTE_MNAR | ||
| - PI | ||
| - QRILC | ||
| - RF | ||
| - ROWMEDIAN | ||
| # - SEQKNN # Error in x[od, ismiss, drop = FALSE]: subscript out of bounds | ||
| - SVDMETHOD | ||
| - TRKNN | ||
| - ZERO | ||
| - BPCA | ||
| - COLMEDIAN | ||
| - IMPSEQ | ||
| - IMPSEQROB | ||
| - IRM | ||
| - KNN_IMPUTE | ||
| - LLS | ||
| # - MICE-CART > 1h20min on GitHub small runner | ||
| # - MICE-NORM ~ 1h on GitHub small runner | ||
| - MINDET | ||
| - MINIMUM | ||
| - MINPROB | ||
| - MLE | ||
| - MSIMPUTE | ||
| - MSIMPUTE_MNAR | ||
| - PI | ||
| - QRILC | ||
| - RF | ||
| - ROWMEDIAN | ||
| # - SEQKNN # Error in x[od, ismiss, drop = FALSE]: subscript out of bounds | ||
| - SVDMETHOD | ||
| - TRKNN | ||
| - ZERO |
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