scgnn2 Config

This is the config for scgnn2.

examples/tuning/imputation_scgnn2/human_melanoma_data/pipeline_params_tuning_config.yaml

---
type: preprocessor
tune_mode: pipeline_params
pipeline_tuning_top_k: 5
parameter_tuning_freq_n: 20
pipeline:
  - type: filter.cell
    target: FilterCellTransform
    params:
      species: human
      image_save_path: ../figures/human_melanoma_data/
      log_level: INFO
  - type: filter.gene
    target: FilterGenesScanpyOrder
    params:
      order: [min_counts, min_cells]
      min_counts: 5
      min_cells: 3
  - type: filter.cell
    target: ScrubletTransform
    params:
      image_save_path: ../figures/human_melanoma_data/
  - type: filter.gene
    include: [FilterGenesTopK]
    default_params:
      FilterGenesTopK:
        num_genes: 2000
        mode: var
    step3_frozen: true
  - type: split.entry
    target: CellwiseMaskData
    params:
      add_test_mask: true
  - type: normalize
    include:
      - ColumnSumNormalize
      - ScTransform
      - Log1P
      - NormalizeTotal
      - NormalizePlaceHolder
      - NormalizeTotalLog1P
    default_params:
      ScTransform:
        processes_num: 8
  - type: misc
    target: SetConfig
    params:
      config_dict:
        feature_channel: [train_mask, valid_mask, test_mask]
        feature_channel_type: [layers, layers, layers]
wandb:
  entity: xzy11632
  project: dance-dev
  method: grid  # try grid to provide a comprehensive search
  metric:
    name: MRE
    goal: minimize