Cytometry inputs and parameters
File formats, marker panels, FlowSOM clustering parameters, and segmentation options for the cytometry tools.
Retired tools
flow_gate, flow_cluster and flow_differential are retired and can no longer be run. For FCS clustering use flowsom, which runs real FlowSOM SOM + consensus metaclustering. There is no hosted tool for automated gating, PhenoGraph clustering or differential abundance; ask Ivy to run those in Python in the chat's code workspace, using flowsom for the cluster labels if you need them.
You provide single-cell cytometry data — FCS event files for flow and mass cytometry, or multi-channel TIFF/MCD acquisitions for imaging mass cytometry. The marker panel you include is what most shapes the result, since every cluster and spatial call is defined by the markers present.
Documented parameters go beyond the implemented tools
The IMC tables below describe the intended parameter surface. imc_segment and imc_spatial as currently registered accept only a file key and an optional panel CSV. The flowsom parameters are the ones in its tool schema.
Cytometry inputs and parameters
Common file formats
| Tool | Accepted Formats | Description |
|---|---|---|
flowsom | FCS | Flow/mass cytometry event data |
imc_segment | Multi-channel TIFF, MCD | Imaging mass cytometry acquisitions |
imc_spatial | CSV | Cell data with X/Y coordinates and type labels |
FCS file requirements
- FCS 3.0 or 3.1 format
- Flow cytometry data should be compensated before upload
- CyTOF data does not require compensation
- Maximum file size: 500 MB per file
- Maximum events: 10 million per file
FlowSOM parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
fcs_key | string | Yes | -- | Key of the uploaded FCS file to cluster |
cols_to_use | string[] | No | All channels | Channel or marker names to cluster on |
cols_indices | integer[] | No | All channels | Channel indices to cluster on, as an alternative to cols_to_use |
xdim | integer | No | 10 | SOM grid width (2-50). Larger gives finer-grained clusters |
ydim | integer | No | 10 | SOM grid height (2-50) |
n_clusters | integer | No | 10 | Number of consensus metaclusters (2-100) |
seed | integer | No | 42 | Random seed for reproducibility |
generate_plot | boolean | No | true | Render a star plot of the SOM grid |
max_events | integer | No | -- | Subsample cap for very large files (at least 1000) |
IMC Segment parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
image | file | Yes | -- | Multi-channel TIFF or MCD file |
method | string | No | "cellpose" | Segmentation method |
nuclear_markers | string[] | Yes | -- | Channel names for nuclear signal |
membrane_markers | string[] | No | -- | Channel names for membrane signal |
min_area | integer | No | 50 | Minimum cell area in pixels |
max_area | integer | No | 5000 | Maximum cell area in pixels |
pixel_size | number | No | 1.0 | Pixel size in microns |
expand_radius | integer | No | 3 | Pixels to expand from nucleus to estimate cell boundary |
normalize | boolean | No | true | Percentile-normalize marker intensities |
Segmentation methods
| Method | Code | Description | Speed | Accuracy |
|---|---|---|---|---|
| Cellpose | cellpose | Deep learning, handles diverse morphologies | Moderate | High |
| DeepCell/Mesmer | deepcell | Optimized for tissue with nuclear + membrane | Moderate | High |
| Watershed | watershed | Classical marker-controlled watershed | Fast | Moderate |
IMC Spatial parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
cell_data | file | Yes | -- | CSV with cell coordinates, types, and marker intensities |
analysis_type | string | No | "neighborhood" | Analysis type |
cell_type_column | string | No | "cell_type" | Column containing cell type labels |
x_column | string | No | "x" | Column containing X coordinates |
y_column | string | No | "y" | Column containing Y coordinates |
radius | number | No | 30 | Neighborhood radius in microns |
permutations | integer | No | 1000 | Number of permutations for significance testing |
cell_types | string[] | No | All types | Cell types to include in analysis |
min_cells | integer | No | 10 | Minimum cells of a type to include in analysis |
Analysis types
| Type | Code | Description |
|---|---|---|
| Neighborhood | neighborhood | Cell type enrichment/depletion within radius |
| Interaction | interaction | Pairwise cell-cell contact frequency |
| Spatial statistics | spatial_stats | Ripley's K/L, nearest-neighbor, Moran's I |
| Community | community | Recurring multi-cell neighborhood patterns |
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