## cellcycle_plot()


Plot cell cycle phases in a 2x2 subplot grid with statistical analysis.


Usage

``` python
cellcycle_plot(
    df,
    conditions,
    condition_col="condition",
    selector_col="cell_line",
    selector_val=None,
    title=None,
    fig_size=(6, 6),
    size_units="cm",
    colors=None,
    save=True,
    save_stats=False,
    path=None,
    tight_layout=False,
    file_format="pdf",
    dpi=300,
    show_significance=True,
    show_repeat_points=True,
    rotation=45,
    cc_phases=True,
    show_subG1=False,
    show_plate_legend=False,
    paired=True,
    show_ns=True,
    min_effect=None
)
```


This is a backward-compatible wrapper around the new class-based architecture. Creates a 2x2 subplot grid showing each cell cycle phase (G1, S, G2/M, Polyploid) separately with repeat points and significance marks.

## Notes

Unlike other plot functions, this returns (Figure, list of Axes) because it creates multiple subplots that cannot be collapsed into a single axis.


Data Filtering df : pd.DataFrame DataFrame containing cell cycle data with required columns: 'cell_cycle', 'plate_id', and condition_col. conditions : list\[str\] List of condition names to plot. condition_col : str, default="condition" Column name for experimental condition. selector_col : str \| None, default="cell_line" Column name for selector (e.g., cell line). selector_val : str \| None, default=None Value to filter selector_col by.

Display Options ^ cc_phases : bool, default=True If True, use cell cycle terminology {Sub-G1, G1, S, G2/M, Polyploid}. If False, use DNA content terminology {\<2N, 2N, S, 4N, \>4N}. show_subG1 : bool, default=False Whether to include Sub-G1/\<2N phase in the plot. show_significance : bool, default=True Whether to show significance marks (requires ≥3 plates). paired : bool, default=True Use a paired t-test (ttest_rel, matched by plate_id) per phase; set False for the unpaired ttest_ind. show_repeat_points : bool, default=True Whether to show individual repeat points. show_plate_legend : bool, default=False Whether to show legend with different shapes for each plate_id.

Styling & Colors title : str \| None, default=None Plot title. If None, generates default title. fig_size : tuple\[float, float\], default=(6, 6) Dimensions of the figure. size_units : str, default="cm" Units of the figure size ("cm" or "inch"). colors : list\[str\] \| None, default=None List of colors for plotting. If None, uses default phase colors: G1=PINK, S=LIGHT_BLUE, G2/M=YELLOW, Polyploid=BLUE. rotation : int, default=45 Rotation angle for x-axis labels. tight_layout : bool, default=False Whether to use tight layout.

Save Options save : bool, default=True Whether to save the figure. save_stats : bool, default=False Write {title}\_stats.csv and {title}\_medians.csv to `path` (independent of `save`; works when plotting onto a provided/composed `axes`). path : Optional\[Path\], default=None Path to save the figure. file_format : str, default="pdf" Format of the figure ("pdf", "png", "svg", etc.). dpi : int, default=300 Resolution of the figure.


tuple\[Figure, list\] The figure object and list of 4 axes objects \[top-left, top-right, bottom-left, bottom-right\].


``` python
>>> fig, axes = cellcycle_plot(
...     df=data,
...     conditions=["control", "treatment"],
...     selector_val="MCF10A",
...     save=False
... )
>>> plt.show()
```

``` python
>>> # Custom colors
>>> fig, axes = cellcycle_plot(
...     df=data,
...     conditions=["ctrl", "drug1", "drug2"],
...     colors=["red", "green", "blue", "purple"],
...     title="Custom Cell Cycle Analysis"
... )
```