Skills

A skill is a package of structured files that teaches an AI coding agent how to work with a specific tool or framework. The skill below was generated by Great Docs from this project’s documentation. Install it in your agent and it will be able to run commands, edit configuration, write content, and troubleshoot problems without step-by-step guidance from you.

Any agent — install with npx:

npx skills add https://hocheggerlab.github.io/omero-screen/plots/

Codex / OpenCode

Tell the agent:
Fetch the skill file at https://hocheggerlab.github.io/omero-screen/plots/skill.md and follow the instructions.

Manual — download the skill file:

curl -O https://hocheggerlab.github.io/omero-screen/plots/skill.md

Or browse the SKILL.md file.

SKILL.md

---
name: omero-screen-plots
description: >
  Add your description here. Use when writing Python code that uses the omero_screen_plots package.
compatibility: Requires Python >=3.12,<3.15.
---

# OMERO-Screen Plots

Add your description here

## Installation

```bash
pip install omero-screen-plots
```

## API overview

### Cell cycle

Phase distributions and stacked composition plots.

- `cellcycle_plot`: Plot cell cycle phases in a 2x2 subplot grid with statistical analysis
- `cellcycle_stacked`: Create a stacked barplot for cell cycle phase proportions with flexible display modes
- `combplot_cellcycle`: Create a combined plot with histograms, scatter plots, and cell cycle barplot

### Counts and features

Cell counts, per-feature comparisons and normalisation.

- `count_plot`: Plot normalized or absolute counts with optional grouping
- `feature_plot`: Plot a unified feature plot with box/violin plots and optional scatter points
- `feature_norm_plot`: Create a normalized feature plot with threshold-based stacked bars
- `combplot_feature`: Create a combined plot with histograms and scatter plots for feature analysis
- `PlotType`: Enumeration for plot types: normalised and absolute

### Distributions

Histograms and scatter plots of single-cell measurements.

- `histogram_plot`: Create histogram plot(s) for single or multiple conditions
- `scatter_plot`: Create a scatter plot with flexible configuration

### Classification and QC

Classifier output and per-well quality control.

- `classification_plot`: Create a classification plot with flexible display options
- `well_qc_plot`: Build a compact per-well QC figure (histogram + scatter + cell-cycle bar)

### Utilities

- `save_fig`: Save a matplotlib figure to a file

## Resources

- [Full documentation](https://hocheggerlab.github.io/omero-screen/plots/)
- [llms.txt](llms.txt) — Indexed API reference for LLMs
- [llms-full.txt](llms-full.txt) — Comprehensive documentation for LLMs