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nf-params.yml
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nf-params.yml
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## ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## SysBioOncology/SPoTLIghT 1.0dev
## ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## This is an example parameter file to pass to the `-params-file` option
## of nextflow run with the SysBioOncology/SPoTLIghT pipeline.
##
## Uncomment lines with a single '#' if you want to pass the parameter to
## the pipeline.
## -----------------------------------------------------------------------------
## -----------------------------------------------------------------------------
## GENERAL OPTIONS
## -----------------------------------------------------------------------------
spotlight_modules: "extracthistopatho,predicttiles,computespatial"
clinical_files_input: "assets/NO_FILE"
cancer_type: "SKCM"
slide_type: "FFPE"
is_tcga: false
is_tumor: true
## -----------------------------------------------------------------------------
## Extracting histopathological features
## -----------------------------------------------------------------------------
# Files and directories
path_codebook: "assets/codebook.txt"
clinical_file_out_file: "generated_clinical_file"
image_dir: "data_example/xenium_images"
checkpoint_path: "assets/checkpoint/Retrained_Inception_v4/model.ckpt-100000"
path_tissue_classes: "assets/tissue_classes.csv"
# Parameters
tumor_purity_threshold: 80
gradient_mag_filter: 20
n_shards: 320
bot_out_filename: "bot_train"
pred_out_filename: "pred_train"
model_name: "inception_v4"
## -----------------------------------------------------------------------------
## Immune deconv bulkRNAseq
## -----------------------------------------------------------------------------
# gene_exp_path: "data_example/TCGA_SKCM_expression/SKCM.rnaseqv2__illuminahiseq_rnaseqv2__unc_edu__Level_3__RSEM_genes__data.data.txt"
# is_tpm: false
# quantiseq_path: "assets/NO_FILE"
# epic_path: "assets/NO_FILE"
# mcp_counter_path: "assets/NO_FILE"
# xcell_path: "assets/NO_FILE"
# mcp_probesets: "assets/mcp_counter/probesets.txt"
# mcp_genes: "assets/mcp_counter/genes.txt"
## -----------------------------------------------------------------------------
## Building multi-task cell type models
## -----------------------------------------------------------------------------
# Files and directories
# clinical_file_path: "output_test_tcga/1_extract_histopatho_features/generated_clinical_file.txt"
# thorsson_scores_path: "assets/local/Thorsson_Scores_160_Signatures.tsv"
# estimate_scores_path: "assets/local/skin_cutaneous_melanoma_RNAseqV2.txt"
# absolute_tumor_purity_path: "assets/local/TCGA_ABSOLUTE.txt"
# gibbons_scores_path: "assets/local/Gibbons.xlsx"
# mfp_gene_signatures: "assets/gene_signatures.gmt"
# bottleneck_features_path: "output_test_tcga/1_extract_histopatho_features/bot_train.txt"
# var_names_path: "assets/task_selection_names.pkl"
# target_features_path: "assets/NO_FILE"
# model_cell_types: "CAFs,endothelial_cells,T_cells,tumor_purity"
# # # Parameters
# alpha_min: -4
# alpha_max: -1
# n_steps: 40
n_outerfolds: 5
# n_innerfolds: 10
# n_tiles: 50
# split_level: "sample_submitter_id"
## -----------------------------------------------------------------------------
## Predict tile-level cell type abundance
## -----------------------------------------------------------------------------
celltype_models_path: "assets/TF_models/SKCM_FF"
prediction_mode: "test"
cell_types_path: "assets/NO_FILE"
is_model_dir: 1
## -----------------------------------------------------------------------------
## Computing spatial features
## -----------------------------------------------------------------------------
# Prefix for spatial features output filenames, else 'slide_type' is used
out_prefix: "dummy"
tile_level_celltype_predictions: "assets/NO_FILE"
# Spatial features parameters
graphs_path: "assets/NO_FILE"
abundance_threshold: 0.5
shapiro_alpha: 0.05
cutoff_path_length: 2
n_clusters: 8
max_dist: "dummy"
max_n_tiles_threshold: 2
tile_size: 512
overlap: 50
metadata_path: "assets/NO_FILE"
merge_var: "slide_submitter_id"
sheet_name: "dummy"