nf-core pipeline ·
nf-core/cellpainting
Processes Cell Painting microscopy assays through illumination correction, feature extraction, and quality control.
What nf-core/cellpainting is
nf-core/cellpainting is a bioinformatics pipeline designed for scalable and reproducible image-based profiling of Cell Painting assays. Originally written by Kenneth Brewer, it processes high-content microscopy images through standard morphological profiling workflows.
The pipeline addresses the computational challenges of high-content screening by standardising illumination correction, automated cell segmentation, quantitative morphological feature extraction, and quality control across experimental batches and multi-well plates.
What the pipeline does
The workflow reads image metadata from a tall-format CSV samplesheet mapping individual TIFF images to channels, plates, wells, and sites. CellProfiler computes illumination correction functions per channel and plate, then segments a single site per well to enable visual quality control.
In the default analysis mode, CellProfiler extracts morphological features across all sites, CytoTable converts the resulting CSV files into analysis-ready Parquet tables, and MultiQC compiles quality control metrics into a final report. When run in assay development mode, the workflow terminates after illumination correction and single-site quality control, bypassing full feature extraction.
Key facts
- Pipeline framework
- Nextflow
- Original developer
- Kenneth Brewer
- Core software
- CellProfiler, CytoTable, MultiQC
- Input formats
- TIFF (.tif, .tiff), CSV samplesheet
- Output formats
- Parquet, MultiQC HTML report
- Execution modes
- analysis, assay_development
What you can use it for
- High-content morphological profiling
- Process multi-channel fluorescence microscopy plates to extract detailed morphological features and export them into Parquet tables for downstream analysis.
- Assay development and quality inspection
- Run in assay_development mode to generate illumination correction functions and visual segmentation previews without executing full feature extraction.
- Quality control aggregation
- Summarise assay-wide quality metrics across plates, batches, and wells using automated MultiQC reporting.
Run it here
The research agent runs nf-core/cellpainting with Nextflow on its own machine — up to 32 cores, 256 GiB of memory and 24 hours per run, which covers the test profile and real single-sample runs. It builds the samplesheet, checks it against the pipeline's schema and reads the results back. When a run is too big for one machine, it gives you the exact command for your own cluster instead.
Strengths and limits
Good at
- Provides a dedicated assay development mode to verify illumination correction and segmentation quality prior to running full analyses.
- Converts CellProfiler CSV outputs into Parquet format using CytoTable for downstream data processing.
- Aggregates image-based quality metrics into unified MultiQC reports.
Watch out for
- Restricted to microscopy image inputs provided in TIFF format (.tif or .tiff).
- Requires metadata to be structured as a tall-format samplesheet containing channel, plate, well, and coordinate positions for every image.
- Pipeline parameters cannot be supplied via custom Nextflow configuration files and must be specified using CLI arguments or parameter files.
Questions
Can I run nf-core/cellpainting without my own cluster?
The research agent runs nf-core/cellpainting with Nextflow on its own machine — up to 32 cores, 256 GiB of memory and 24 hours per run, which covers the test profile and real single-sample runs. It builds the samplesheet, checks it against the pipeline's schema and reads the results back. When a run is too big for one machine, it gives you the exact command for your own cluster instead.
What licence is nf-core/cellpainting under?
MIT, like every nf-core pipeline.
What input file formats does the pipeline require?
The pipeline expects microscopy images in .tif or .tiff format, accompanied by a tall-format CSV samplesheet containing channel, plate, well, site, and coordinate metadata.
What is the difference between analysis and assay_development modes?
The assay_development mode stops after calculating illumination correction and segmenting a single site per well for visual quality inspection. The analysis mode runs the complete pipeline, including whole-site morphological feature extraction and Parquet conversion.
Which tool handles the conversion to Parquet files?
CytoTable converts the CSV tables produced by CellProfiler into analysis-ready Parquet files.
How are quality control metrics reported?
Quality control metrics generated across the processing steps are collated into a summary report using MultiQC.
How to cite it
Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen. The nf-core framework for community-curated bioinformatics pipelines. Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.
Written from nf-core/cellpainting's own README. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.