Capabilities

spaCR follows an image-based screen from raw microscopy files to a ranked hit list. This page gives the full map; the Python API quickstart and interactive tutorials show the individual routes.

Core screen workflow

Mask

Mask prepares TIFF, OME-TIFF, LIF, CZI and ND2 acquisitions and segments cells, nuclei, pathogens and organelles with Cellpose. It supports 2-D, volumetric and time-series data, estimates object diameter, and can exchange mask corrections with the layer viewer or napari.

The objects are not a fixed set of four. A project has a cell, a nucleus and a pathogen, a cytoplasm derived from them, and as many organelle slots as number_of_organelles asks for – from none up to twenty-six. Each slot is independent, with its own channel, diameter, detection method and morphology.

A slot is given a morphology preset – punctate, vesicular, spherical, filamentous, tubular, reticular, cisternal, toroidal, crescent, or custom – and the preset chooses the detection strategy, one of spots, network, irregular or ring.

Measure

Measure writes per-object morphology, intensity, texture, radial, spatial and colocalization features to measurements.db. It can save classifier-ready object crops, estimate illumination correction from a plate, restrict work to a region of interest and report segmentation quality before a run.

Annotate and Classify

Annotate provides a keyboard-driven crop grid, records labels directly in the project database and can rank an active-learning queue by uncertainty. Classify trains PyTorch image models or classical and boosted models from measurement tables. Checkpoints record their dataset, split rule, class balance and held-out metrics.

Map Barcodes

Barcode mapping decodes row, column and gRNA barcodes from FASTQ reads, joins them to imaged wells and reports abundance, collision, unmapped-read and library-coverage checks.

Regression

Regression estimates guide, gene, condition and control effects. Its model families cover continuous, fractional, binary and count responses, robust and quantile fits, penalised high-dimensional designs, mixed effects and guide permutation. Diagnostics and run summaries are written beside the result.

Planning, quality control and exploration

• Power and Design estimate cell and well requirements and lay out plates, controls and replicates.

• QC Dashboard combines segmentation, plate, annotation-agreement and leakage checks.

• Batch correction provides centering, z-scoring, robust z-scoring, control centering and ComBat with protected biological covariates.

• Graph Builder, gates and linked views connect summary plots to the object crops behind them.

• Feature, dose-response, control-chart and outlier views inspect a result without an export/re-import cycle.

• Layer and lineage views connect images, masks and the cell → nucleus → pathogen object hierarchy.

Reproducibility and interoperability

Every run can record its identifier, seed, resolved settings and outputs. Interrupted workflows can resume from checkpoints, and the run history can compare settings and artefacts. Measurements export to AnnData; optional integrations read or write OME-Zarr, connect to OMERO and send masks to napari.

How a module is reached

The home screen groups modules into four categories – Core, Data, Tools and Assays – and twenty-one modules have a tile in one of them. Core is the pipeline you run in order; Data is what goes in and what comes out of it; Tools are the instruments you point at a project rather than steps the pipeline takes on its own; Assays are the quantitative readouts. Make Masks is filed under Tools.

A TILE IS NOT THE ONLY WAY IN, and most modules do not have one. A tile says “start here”, and a module that answers a question about a run somebody else started is not a place to start. Those open instead from:

• a button on their host’s masthead – as a page beside that host’s settings, already pointed at the same project. Investigate Hit and Prediction Profiler open from Regression; Format Converter and External Masks from Import; Layer Viewer, Control Charts and Outliers from QC.

• the Help menu, for the ones that inspect or administer work that already exists rather than belonging behind any one module – Run History, Pipeline Graph, Project Browser, Database Browser, Report, Data Manager, Plate Queue, Batch Runner and Distributed Jobs.

• the command palette (Ctrl+K), which reaches EVERY module, tiled or not. It is the one route with no exceptions, and the keyboard user’s navigation.

None of them is second-class: they are shipped, translated and documented like any other module, and the ones that are pipelines still run headlessly under spacr-run.

Host	Opens from its masthead
Mask	Timelapse
Measure	Illumination Correction, AnnData Export, Motility Assay
Annotate	Annotator Agreement
Classify	Classifier Evaluation, Explain CV Model, Activation Maps
Map Barcodes	Barcode QC
Regression	Volcano Explorer, Hit List, Methods & Results
Image UMAP	Image Scatter, PCA
Make Masks	Cellpose Workbench, Mask the whole folder, Model Compare, Model Zoo, Curate, Napari Bridge

Parameter Sweep is reached a third way: it is a panel on the Regression screen, opened by the Parameter sweep switch on its settings form.

Make Masks

Make Masks corrects masks by hand and carries the Cellpose loop on its masthead. Its canvas has nine tools: Brush, Erase, Erase object, Wand +, Wand −, Draw, Divide, Zoom and Recrop.

Draw traces a free-form outline that closes and fills as a single object – the tool a brush is not, because a brush stamps disks along the path, so tracing a rim with it labels the rim and leaves the middle background. Divide drags a line across a merged object and makes it two, leaving every other object’s label untouched; it is the commonest correction a segmentation needs.

Recrop is the only tool that changes which field is on screen rather than what is painted on it. A staged crop holding several cells is not one training example, and curating it as one teaches a network that two objects are one picture – so a box round an object writes that region of both the image and the mask as a field of its own, queued straight after the current one, and the multi-object original is retired into recropped_originals/ rather than curated. A box smaller than the minimum side, or one repeating a cut already made, is refused; objects the box cuts through are dropped, because an object whose boundary is where the mouse was released is not that object; and the labels that survive are renumbered from one.

Running Cellpose-SAM from this screen shows its two intermediate outputs beside the mask: the cell-probability map and the flow field. A mask is a threshold applied to that probability map, and a candidate object is discarded when its flows disagree with the ones the network predicted by more than the flow-error threshold. When a mask is wrong, those two panes are where the reason is visible.

Settings that apply

The settings panel carries a control when it applies to the run being set up and leaves it off the form when it does not:

• a slot past number_of_organelles takes its whole block of settings with it, its channel included – a slot the run does not have is not a slot with its channel left showing;

• an object whose channel names no plane is not in the run at all, so its settings are not on the form;

• a setting belonging to one morphology is dropped for a slot of another: a punctate organelle has no ridge filter.

The 3D and Time switches declare which dimensions the plate has. z_stack declares a z axis and enables the volumetric settings – segmentation mode, anisotropy and voxel size – and stops with an error rather than guessing which axis is z. timelapse declares a time axis and reveals tracking; a single-timepoint plate ignores it. The 4D settings apply only when the data is both a z-stack and a time series, and appear only then.

Maturity labels

The API uses these labels consistently:

Stable

Supported entry points used by the principal Mask, Measure, Classify, barcode and regression workflows. Backward-incompatible changes require a deprecation period.

Advanced

Supported specialist functionality whose defaults or result schema may still evolve. Release notes describe material changes.

Experimental

Early interfaces intended for evaluation. They may change between minor releases and should be pinned before use in an automated workflow.

Internal

GUI widgets, workers and implementation helpers. They are documented for contributors but are not a compatibility promise.

Optional dependencies

The base package contains the headless pipelines. Install spacr[qt] for the desktop interface. Other extras add OME-Zarr, OMERO, napari, attribution, tracking, Zernike measurements and vendor readers. Availability varies with Python version; the installer guide is the authoritative compatibility table.