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cellpose_baysor.yaml
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cellpose_baysor.yaml
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# For parameters details, see this commented example: https://github.com/gustaveroussy/sopa/blob/master/workflow/config/example_commented.yaml
read:
technology: xenium
patchify:
patch_width_pixel: 6000
patch_overlap_pixel: 150
patch_width_microns: 1000
patch_overlap_microns: 20
segmentation:
cellpose:
diameter: 30
channels: ["DAPI"] # among "DAPI", "ATP1A1/CD45/E-Cadherin", "18S", "AlphaSMA/Vimentin"
flow_threshold: 2
cellprob_threshold: -6
min_area: 400
baysor:
min_area: 20
config:
data:
force_2d: true # if false, uses 3D mode
min_molecules_per_cell: 10
x: "x"
y: "y"
z: "z"
gene: "feature_name"
min_molecules_per_gene: 0
min_molecules_per_segment: 3
confidence_nn_id: 6
segmentation:
scale: 6.25 # typical cell radius
scale_std: "25%" # cell radius standard deviation
prior_segmentation_confidence: 1 # confidence of the cellpose confidence (float in [0, 1])
estimate_scale_from_centers: false
n_clusters: 4
iters: 500
n_cells_init: 0
nuclei_genes: ""
cyto_genes: ""
new_component_weight: 0.2
new_component_fraction: 0.3
aggregate:
average_intensities: true
min_transcripts: 10 # [optional] cells whose transcript count is below that this threshold are filtered
# Comment this out if you want to use tangram -->
# annotation:
# method: tangram
# args:
# sc_reference_path: "..."
# cell_type_key: ct
explorer:
gene_column: "feature_name"
ram_threshold_gb: 4
executables:
baysor: ~/.julia/bin/baysor # if you run baysor, put here the path to the baysor executable