## combplot_feature()


Create a combined plot with histograms and scatter plots for feature analysis.


Usage

``` python
combplot_feature(
    df,
    conditions,
    feature,
    threshold=None,
    condition_col="condition",
    selector_col="cell_line",
    selector_val=None,
    title=None,
    cell_number=3000,
    fig_size=None,
    size_units="cm",
    save=True,
    path=None,
    file_format="png",
    dpi=300,
    figure=None,
    show_ylabel=True,
    show_xlabel=True
)
```


Creates a `(2 + n_features)×n_conditions` grid layout that grows vertically with the number of features supplied:

- Top row: DNA content histograms for each condition.
- Second row: DNA vs EdU scatter plots with cell cycle phases.
- One additional row per feature: DNA vs feature scatter plots with optional threshold colouring.

Passing a single `feature` string reproduces the classic three-row layout (histogram → EdU → feature); passing a list of features stacks one scatter row per feature underneath the EdU row.


Data Filtering df : pd.DataFrame DataFrame containing single-cell measurements. 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.

Plot Configuration feature : str \| list\[str\] Feature column name(s) for the stacked scatter rows. A single string creates one feature row; a list creates one row per entry, in order. threshold : float \| list\[float \| None\] \| None, default=None Threshold value(s) for feature colouring (below=blue, above=red). A scalar (or `None`) is applied to every feature row; a list must match the length of `feature`, with `None` entries disabling the threshold for that row. cell_number : Optional\[int\], default=3000 Number of cells to sample per condition for plotting.

Styling & Layout title : Optional\[str\], default=None Plot title. If None, generates default title. fig_size : Optional\[tuple\[float, float\]\], default=None Figure size as (width, height). When `None` the height scales with the number of rows (matching the classic `(10, 7)` default for a single feature). 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.


Classic single-feature layout:

``` python
>>> fig, axes = combplot_feature(
...     df=data,
...     conditions=["control", "treatment1", "treatment2"],
...     feature="intensity_mean_p21_nucleus",
...     threshold=5000,
...     selector_col="cell_line",
...     selector_val="MCF10A",
... )
```

Stack several features as extra rows (one threshold per feature, `None` to disable):

``` python
>>> fig, axes = combplot_feature(
...     df=data,
...     conditions=["control", "treatment1"],
...     feature=[
...         "intensity_mean_p21_nucleus",
...         "intensity_mean_p53_nucleus",
...         "area_cell",
...     ],
...     threshold=[5000, 3000, None],
...     selector_col="cell_line",
...     selector_val="MCF10A",
... )
```