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xingzhongyuxingzhongyu
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update dataset
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‎.gitignore‎

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@@ -90,6 +90,7 @@ examples/tuning/joint_embedding_scmogcn/models/model_joint_embedding_1.pth
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!examples/tuning/deconv_spotlight/hcc_liver/**
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!examples/tuning/deconv_stdgcn/hcc_liver/**
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!examples/tuning/deconv_dstg/hcc_liver/**
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!examples/tuning/joint_embedding_dcca/GSE140203_SKIN_atac2gex/**
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!examples/tuning/joint_embedding_jae/GSE140203_SKIN_atac2gex/**
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‎examples/tuning/joint_embedding_dcca/GSE140203_SKIN_atac2gex/config_yamls/params/0_test_acc_params_tuning_config.yaml‎

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---
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type: preprocessor
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tune_mode: params
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pipeline:
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- type: filter.gene
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target: FilterGenesScanpyOrder
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params_to_tune:
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order:
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values:
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- - min_counts
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- min_cells
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- max_counts
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- max_cells
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- - min_counts
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- min_cells
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- max_cells
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- max_counts
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- - min_counts
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- max_counts
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- min_cells
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- max_cells
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- - min_counts
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- max_counts
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- max_cells
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- min_cells
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- - min_counts
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- max_cells
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- min_cells
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- max_counts
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- - min_counts
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- max_cells
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- max_counts
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- min_cells
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- - min_cells
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- min_counts
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- max_counts
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- max_cells
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- - min_cells
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- min_counts
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- max_cells
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- max_counts
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- - min_cells
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- max_counts
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- min_counts
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- max_cells
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- - min_cells
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- max_counts
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- max_cells
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- min_counts
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- - min_cells
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- max_cells
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- min_counts
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- max_counts
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- - min_cells
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- max_cells
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- max_counts
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- min_counts
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- - max_counts
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- min_counts
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- min_cells
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- max_cells
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- - max_counts
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- min_counts
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- max_cells
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- min_cells
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- - max_counts
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- min_cells
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- min_counts
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- max_cells
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- - max_counts
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- min_cells
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- max_cells
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- min_counts
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- - max_counts
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- max_cells
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- min_counts
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- min_cells
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- - max_counts
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- max_cells
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- min_cells
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- min_counts
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- - max_cells
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- min_counts
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- min_cells
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- max_counts
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- - max_cells
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- min_counts
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- max_counts
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- min_cells
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- - max_cells
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- min_cells
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- min_counts
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- max_counts
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- - max_cells
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- min_cells
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- max_counts
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- min_counts
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- - max_cells
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- max_counts
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- min_counts
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- min_cells
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- - max_cells
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- max_counts
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- min_cells
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- min_counts
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min_counts:
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min: 3
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max: 500
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min_cells:
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min: 0.0
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max: 0.1
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max_counts:
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min: 0.9
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max: 1.0
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max_cells:
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min: 0.95
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max: 1.0
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params:
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mod: mod1
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- type: filter.gene
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target: FilterGenesPlaceHolder
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params:
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mod: mod2
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- type: misc
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target: AlignMod
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- type: normalize
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target: NormalizePlaceHolder
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params:
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mod: mod1
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- type: normalize
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target: NormalizePlaceHolder
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params:
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mod: mod2
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- type: normalize
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target: Log1P
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params_to_tune:
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base:
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min: 1.0
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max: 10.0
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params:
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mod: mod1
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- type: normalize
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target: Log1P
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params_to_tune:
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base:
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min: 1.0
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max: 10.0
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params:
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mod: mod2
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- type: filter.gene
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target: FilterGenesRegression
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params_to_tune:
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method:
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values: [enclasc, seurat3, scmap]
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num_genes:
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min: 100
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max: 10000
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params:
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mod: mod1
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channel: counts
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channel_type: layers
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- type: filter.gene
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target: FilterGenesRegression
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params_to_tune:
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method:
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values: [enclasc, seurat3, scmap]
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num_genes:
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min: 100
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max: 10000
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params:
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mod: mod2
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channel: counts
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channel_type: layers
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- type: filter.cell
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target: FilterCellsPlaceHolder
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params:
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mod: mod1
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- type: filter.cell
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target: FilterCellsScanpyOrder
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params_to_tune:
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order:
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values:
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- - min_counts
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- min_genes
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- max_counts
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- max_genes
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- - min_counts
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- min_genes
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- max_genes
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- max_counts
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- - min_counts
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- max_counts
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- min_genes
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- max_genes
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- - min_counts
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- max_counts
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- max_genes
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- min_genes
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- - min_counts
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- max_genes
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- min_genes
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- max_counts
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- - min_counts
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- max_genes
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- max_counts
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- min_genes
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- - min_genes
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- min_counts
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- max_counts
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- max_genes
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- - min_genes
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- min_counts
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- max_genes
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- max_counts
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- - min_genes
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- max_counts
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- min_counts
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- max_genes
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- - min_genes
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- max_counts
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- max_genes
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- min_counts
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- - min_genes
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- max_genes
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- min_counts
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- max_counts
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- - min_genes
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- max_genes
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- max_counts
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- min_counts
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- - max_counts
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- min_counts
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- min_genes
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- max_genes
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- - max_counts
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- min_counts
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- max_genes
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- min_genes
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- - max_counts
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- min_genes
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- min_counts
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- max_genes
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- - max_counts
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- min_genes
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- max_genes
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- min_counts
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- - max_counts
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- max_genes
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- min_counts
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- min_genes
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- - max_counts
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- max_genes
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- min_genes
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- min_counts
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- - max_genes
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- min_counts
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- min_genes
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- max_counts
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- - max_genes
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- min_counts
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- max_counts
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- min_genes
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- - max_genes
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- min_genes
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- min_counts
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- max_counts
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- - max_genes
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- min_genes
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- max_counts
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- min_counts
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- - max_genes
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- max_counts
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- min_counts
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- min_genes
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- - max_genes
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- max_counts
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- min_genes
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- min_counts
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min_counts:
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min: 0.0
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max: 0.05
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min_genes:
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min: 0.0
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max: 0.05
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max_counts:
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min: 0.95
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max: 1.0
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max_genes:
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min: 0.95
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max: 1.0
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params:
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mod: mod2
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- type: filter.cell
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target: FilterCellsCommonMod
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params:
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mod1: mod1
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mod2: mod2
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sol: test_sol
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- type: filter.cell
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target: FilterCellsPlaceHolder
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params:
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mod: meta1
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- type: filter.cell
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target: FilterCellsPlaceHolder
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params:
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mod: meta2
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- type: filter.cell
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target: FilterCellsCommonMod
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params:
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mod1: meta1
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mod2: meta2
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- type: feature.cell
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target: FeatureCellPlaceHolder
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params:
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out: feature.cell
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log_level: INFO
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mod: mod1
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- type: feature.cell
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target: FeatureCellPlaceHolder
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params:
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out: feature.cell
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log_level: INFO
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mod: mod2
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- type: misc
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target: SetConfig
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params:
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config_dict:
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feature_mod: [mod1, mod2, mod1, mod2, mod1, mod2]
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label_mod: mod1
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feature_channel_type: [obsm, obsm, layers, layers, obsm, obsm]
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feature_channel:
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- feature.cell
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- feature.cell
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- counts
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- counts
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- size_factors
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- size_factors
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label_channel: labels
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wandb:
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entity: xzy11632
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project: dance-dev
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method: bayes
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metric:
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name: ARI
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goal: maximize

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