Overview

OmeroScreen Plots is a comprehensive visualization and analysis package for high-content screening data from OMERO. It provides standardized, publication-ready plots for immunofluorescence microscopy data with built-in statistical analysis.

Recent Architecture Update: The package has been refactored from a complex multi-class factory pattern to a simplified single-class architecture, providing better performance, maintainability, and error handling while maintaining full backward compatibility.

Key Features

• Standardized Plots: Consistent, publication-ready figures for screening data
• Multiple Plot Types: Feature plots, cell cycle analysis, combined plots, and more
• Statistical Analysis: Built-in statistical tests and data normalization
• Flexible Customization: Extensive options for colors, grouping, and styling
• Integration: Works seamlessly with OMERO and cellview databases

Quick Start

import pandas as pd
from omero_screen_plots.countplot_api import count_plot
from omero_screen_plots.countplot_factory import PlotType

# Load your data
df = pd.read_csv("path/to/data.csv")

# Create a count plot (simplified architecture)
fig, ax = count_plot(
    df=df,
    norm_control="DMSO",
    conditions=["DMSO", "Treatment1", "Treatment2"],
    condition_col="condition",
    selector_col="cell_line",
    selector_val="MCF10A",
    title="Cell Count Analysis",
    save=True,
    path="output/"
)

Full signatures and parameter documentation for every public function are in the API reference.