experiment.yaml

name: '20180101_codex_mouse_spleen_balbc_slide1'
date: '2018-01-01 00:00:00'
environment:
  path_formats:
    proc_image: 'processor/tile/R{region:02d}_X{x:02d}_Y{y:02d}.tif'
acquisition:
  # Imaging was performed in Keyence BZ-X710 fluorescent microscope configured with 3 fluorescent channels
  # (FITC, Cy3, Cy5) and equipped with Nikon PlanFluor 40x NA 1.3 oil immersion lens
  per_cycle_channel_names: [FITC, Cy3, Cy5]
  channel_names:
    - CD45
    - Ly6C
    - TCR
    - CD45cyc2
    - Ly6G
    - CD19
    - CD45cyc3
    - CD169
    - CD106
    - CD45cyc4
    - CD3
    - CD16_32
    - CD45cyc5
    - CD8a
    - CD90
    - CD45cyc6
    - F4_80
    - CD11c
    - CD45cyc7
    - Ter119
    - CD11b
    - CD45cyc8
    - IgD
    - CD27
    - CD45cyc9
    - CD5
    - CD79b
    - CD45cyc10
    - CD71
    - CD31
    - CD45cyc11
    - CD4
    - IgM
    - CD45cyc12
    - B220
    - ERTR7
    - CD45cyc13
    - MHCII
    - CD35
    - CD45cyc14
    - CD21_35
    - CD44
    - CD45cyc15
    - blank_Cy3_cyc15
    - blank_Cy5_cyc15
    - CD45cyc16
    - blank_Cy3_cyc16
    - blank_Cy5_cyc16
    - CD45cyc17
    - blank_Cy3_cyc17
    - nucl
    - CD45cyc18
    - NKp46
    - blank_Cy5_cyc18
  # These are incorrect, since deconvolution isn't really necessary
  # but there have to be as many of them as there are filters
  emission_wavelengths: [595,595,595]
  # Each tissue was imaged with a 40x oil immersion objective in a 7x9 tiled acquisition at 1386x1008 pixels per
  # tile and 188 nm/pixel resolution and 11 z-planes per tile (axial resolution 900 nm)
  axial_resolution: 900.0
  lateral_resolution: 188.0
  magnification: 40
  num_cycles: 18
  # Paper says 11 z-planes were used but data contains 15 planes
  num_z_planes: 15
  numerical_aperture: 1.3
  objective_type: oil
  region_names: [Region1]
  region_height: 9
  region_width: 7
  tile_height: 1008
  tile_overlap_x: 0
  tile_overlap_y: 0
  tile_width: 1344
  tiling_mode: snake
operator:
  - extract:
      name: segm
      channels:
        - proc_nucl
        - proc_CD45
        - cyto_cell_boundary
        - cyto_nucleus_boundary
      z: all
  - montage: {name: segm, extract_name: segm}
  - extract:
      name: figureset1
      channels:
        - proc_B220
        - proc_CD11c
        - proc_CD169
        - proc_CD4
        - proc_CD45
        - proc_CD5
        - proc_CD8a
        - proc_CD90
        - proc_F4_80
        - proc_IgD
        - proc_MHCII
        - proc_TCR
        - proc_nucl
        - cyto_cell_boundary
        - cyto_nucleus_boundary
  - montage: {name: figureset1, extract_name: figureset1}
  - extract:
      name: cy5
      channels:
        - proc_CD27
        - proc_CD31
        - proc_CD35
        - proc_TCR
        - proc_CD11c
        - proc_nucl
        - cyto_cell_boundary
        - cyto_nucleus_boundary
  - montage: {name: cy5, extract_name: cy5}
analysis:
  - aggregate_cytometry_statistics: {mode: best_z_plane}
  # Uncomment to produce CP exports by default
  # - cellprofiler_quantification: {export_csv: true, export_db: true, export_db_objects_separately: true}
processor:
  args:
    gpus: [0,1]
    # Tiles are already assembled
    run_crop: false
    # *** Change run_tile_generator to true if you've copied this config and are applying it to real data ***
    # --> This is only necessary with CODEX because the publication did not share raw data, only an intermediate
    #     form that is compatible with an intermediate form Cytokit uses, allowing this flag to bypass reading raw images
    run_tile_generator: false
    run_drift_comp: false
    run_cytometry: true
    run_best_focus: true
  best_focus: {channel: nucl}
  drift_compensation: {channel: CD45}
  # Note: Raw data is already deconvolved
  deconvolution: {n_iter: 25, scale_factor: .5}
  tile_generator: {raw_file_type: keyence_rgb}
  cytometry:
    # Downsample by half to get segmentation at 20x
    target_shape: [504, 672]
    nuclei_channel_name: nucl
    segmentation_params: {memb_min_dist: 8, memb_sigma: 5, memb_gamma: .25, marker_dilation: 3}
    quantification_params: {nucleus_intensity: true, cell_graph: true}