deepimpute Config
This is the config for deepimpute.
examples/tuning/imputation_deepimpute/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: misc
target: SaveRaw
- type: normalize
include:
- ColumnSumNormalize
- ScTransform
- Log1P
- NormalizeTotal
- NormalizePlaceHolder
- NormalizeTotalLog1P
default_params:
ScTransform:
processes_num: 8
- type: filter.gene
include: [FilterGenesNumberPlaceHolder]
step3_frozen: true
- type: misc
target: UpdateRaw
# - type: feature.cell
# include:
# - WeightedFeaturePCA
# - WeightedFeatureSVD
# - CellPCA
# - CellSVD
# # - FeatureCellPlaceHolder
# params:
# out: feature.cell
# log_level: INFO
# default_params:
# WeightedFeaturePCA:
# split_name: train
# WeightedFeatureSVD:
# split_name: train
- type: split.gene
target: GeneHoldout
- type: split.entry
target: CellwiseMaskData
params:
add_test_mask: true
- type: misc
target: SetConfig
params:
config_dict:
feature_channel:
- None
- None
- targets
- predictors
- train_mask
- valid_mask
- test_mask
feature_channel_type:
- X
- raw_X
- uns
- uns
- layers
- layers
- layers
label_channel: [None, None]
label_channel_type: [X, raw_X]
wandb:
entity: xzy11632
project: dance-dev
method: grid # try grid to provide a comprehensive search
metric:
name: MRE
goal: minimize