## combplot_cellcycle()


Create a combined plot with histograms, scatter plots, and cell cycle barplot.


Usage

``` python
combplot_cellcycle(
    df,
    conditions,
    condition_col="condition",
    selector_col="cell_line",
    selector_val=None,
    title=None,
    cell_number=3000,
    cc_phases=True,
    show_error_bars=True,
    fig_size=(12, 7),
    size_units="cm",
    save=True,
    path=None,
    file_format="png",
    dpi=300
)
```


Creates a 2×(n_conditions+1) grid layout: - Top row: DNA content histograms for each condition + empty space for barplot - Bottom row: DNA vs EdU scatter plots for each condition + cell cycle stacked barplot


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

Display Options ^ cell_number : Optional\[int\], default=3000 Number of cells to sample per condition for plotting. cc_phases : bool, default=True If True, use cell cycle terminology. If False, use DNA content terminology. show_error_bars : bool, default=True Whether to show error bars on the stacked cell cycle barplot.

Styling & Layout title : Optional\[str\], default=None Plot title. If None, generates default title. fig_size : tuple\[float, float\], default=(12, 7) Figure size as (width, height). size_units : str, default="cm" Units for fig_size ("cm" or "inches").

Save Options save : bool, default=True Whether to save the figure. path : Optional\[Path\], default=None Directory path for saving the figure. file_format : str, default="png" File format for saving ("png", "pdf", "svg", etc.). dpi : int, default=300 Resolution for saved figure.


tuple\[Figure, list\] The figure object and list of axes objects.


``` python
>>> fig, axes = combplot_cellcycle(
...     df=data,
...     conditions=["control", "treatment1", "treatment2"],
...     selector_col="cell_line",
...     selector_val="MCF10A"
... )
```