nf-core/cellpainting
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This project focuses on nf-core/cellpainting, a Nextflow pipeline for scalable, reproducible image-based profiling of Cell Painting assays. The pipeline takes high-content microscopy images, applies illumination correction, extracts morphological features with CellProfiler, and converts the results to analysis-ready Parquet files with CytoTable.

The pipeline already has a working core (illumination correction → assay-development QC → CellProfiler analysis → CytoTable conversion → MultiQC), but it is pre-1.0 and there is a long list of high-value features and polish work to do before a first release. The Boston hackathon is a great chance to broaden the contributor base and knock out a batch of well-scoped issues across the stack.

Goal

Make meaningful progress toward a 1.0 release of nf-core/cellpainting by closing a batch of open issues — adding new analysis modules from the cytomining ecosystem, tightening the test suite, and improving downstream usability of the pipeline outputs.

What participants will do

Each contributor will:

Pick an issue from the nf-core/cellpainting issue tracker and assign themselves.
Discuss the approach with the project lead and other contributors at the table.
Implement the change on a feature branch (new module, test improvement, or documentation update).
Run nf-test and lint locally with the test profile.
Open a Pull Request for review.

Suggested tasks

Good first issue

#40 — Switch CytoTable grouping from per-site to per-plate. Self-contained Nextflow refactor: regroup the CytoTable invocation by (batch, plate) and update the test snapshot. Touches one module, one workflow file, and the docs.

Test infrastructure

#39 — Add a test_full profile that runs a full plate from the minimal test dataset. Generate a full-plate samplesheet for BR00117035, host it on the cellpainting branch of nf-core/test-datasets, and wire up the AWS megatest profile.
#38 — Replace coarse md5 snapshots with intelligent assertions for CellProfiler outputs. Move from blanket file-ignore lists to nf-test path/line assertions that allow non-deterministic fields (run timestamps, work-dir paths, PNG metadata) without losing coverage.
#15 — Add SQLite Cell Painting Gallery example data. Subset the BR00117035.sqlite from the Cell Painting Gallery and contribute it to nf-core/test-datasets.

New modules — cytomining downstream stack

#9 — pycytominer_annotate, #10 — pycytominer_aggregate, #11 — pycytominer_normalize, #12 — pycytominer_featureselect. Add the pycytominer operations as nf-core modules and wire them into the analysis subworkflow downstream of CytoTable.
#8 — cosmicqc. Add coSMicQC as a single-cell QC step.

New modules — imaging

#2 — cellpose. Integrate Cellpose segmentation as an alternative to CellProfiler primary/secondary objects, feeding label matrices into a re-configured analysis pipeline.
#5 — fiji_stitchsegmentedimages. Stitch per-site assay-development overlays into a pseudo-plate view for at-a-glance visual QC.

Who should join?

This project is a good fit for people interested in:

Nextflow / nf-core pipeline development (any experience level)
Image-based profiling, high-content imaging, or Cell Painting assays
The cytomining ecosystem (CellProfiler, CytoTable, pycytominer, coSMicQC)
Test engineering with nf-test
Bringing a new pipeline to its first release

You do not need a biology background — most of the open issues are pure pipeline-engineering tasks.

Recommended preparation

Basic familiarity with Git and GitHub (forks, branches, pull requests)
Some exposure to Nextflow and nf-core (Hello nextflow and Hello nf-core are great primers)
Working Docker or Singularity install for running -profile test,docker
Optional reading: the Cell Painting protocol and the JUMP Cell Painting Consortium overview for context on the data