Welcome to spaCR¶

spaCR — Spatial phenotype analysis of CRISPR screens.

Website: einarolafsson.github.io/projects/spacr

Note

You are reading the nightly documentation for spaCR 1.5.1.4. The main site follows main. The nightly preview follows nightly and may describe features not yet in a release. Each branch publishes its own API, guides and committed tutorial catalog automatically.

A Python toolkit for quantifying and visualising phenotypic changes in high-throughput microscopy screens. It provides a PySide6 desktop interface (spacr), headless pipeline functions (spacr.core), and a workflow from plate images to object classification built on PyTorch, Cellpose, scikit-image and SciPy.

It is built for cell biologists running pooled or arrayed CRISPR screens who need per-cell measurements from plate images. The GUI route needs no programming; the same processing steps are available through the Python API for scripted and reproducible workflows.

The GUI groups its applications into four categories: Core for the segment-measure-classify pipeline; Data for importing images and tables, feature embeddings, run comparison, experiment and power design, dose–response analysis and quality control; Tools for operations on an existing project — hand mask correction, stitching, image UMAP, gating and plotting; and Organism for the Toxoplasma organism guide, which lists its available assays; planned analyses are marked Coming soon. The bands under “Applications and workflow” below are those categories, in that order, with the tiles each one holds.

Not every screen is a tile. Screens used within another step open from that step’s masthead — Timelapse from Mask, Illumination and the Motility Assay from Measure, Classifier Evaluation and Explain CV Model from Classify, Annotator Agreement from Annotate, and the Cellpose Workbench, Model Compare, Model Zoo and Curate from Make Masks, among others. Home shows only the tiles enabled in the running build.

🚀 Get started

Install spaCR from PyPI and launch the Qt GUI in two commands.

https://github.com/EinarOlafsson/spacr#install-spacr

🎓 Interactive tutorials

Narrated, step-by-step lessons for spaCR workflows and modules.

tutorials/

📖 API reference

Supported workflow entry points and the complete module reference.

API reference

🎬 Video tutorials

Narrated walkthroughs of each pipeline module.

tutorials/

🐛 Report an issue

File a bug, request a feature, or ask a question.

https://github.com/EinarOlafsson/spacr/issues/new

Applications and workflow¶

New to spaCR? Choose a workflow after installation for the first Home tile, the inputs each step needs, and what to open next.

Every tile links to the API page used by that application’s in-product help.

spaCR modules¶

Core¶

Core sequence from microscopy images through segmentation, measurements, annotations, classification, barcode mapping and regression.

Data¶

Import images and tables into spaCR projects and execute reproducible multi-plate workflows.

Tools¶

Point these at a project: edit masks by hand, stitch tiles, read an embedding, draw a gate, build a plot, check quality.

Organism¶

Organism-specific image analysis and quantitative assay readouts.

Installation¶

Install spaCR and launch the desktop application. The standard package includes the Qt interface and command-line pipelines.

python -m pip install spacr
spacr                    # launch the Qt GUI

For a terminal workflow on a cluster or server, use spacr-run without opening the desktop application:

python -m pip install spacr
spacr-run --list         # list the headless pipeline modules

Learn spaCR¶

Start with installation, continue to Home and the pipeline overviews, then follow the module walkthrough for your task in the interactive tutorial library. Each lesson lists its available narration voices and captions. New English lessons can appear while their translations are being prepared. Open the library from the GUI through Help → Tutorial.