chrov

Chromosome Visualization library in python.
Examples · Explore the API

🏷️Annotations on chromosomes
🧬Visualization of genome, set of chromosomes, a chromosome and an arm
🔥🗺️Visualization of heatmaps along chromosome arm
🔌Integration of custom plots e.g. made using seaborn
📈🍭Integration of basic plots e.g. stem/lollipop plot
↔️↔️Visualization of intervals/ranges/segments along a chromosome arm

pip install chrov              # with basic dependencies  

With additional dependencies as required:

pip install chrov[dev]         # for local testing

1. Using BibTeX:

@software{Dandage_chrov,
  title   = {chrov: Chromosome Visualization library in python},
  author  = {Dandage, Rohan},
  year    = {2023},
  url     = {https://zenodo.org/doi/10.5281/zenodo.10211265},
  version = {v0.0.1},
  note    = {The URL is a DOI link to the permanent archive of the software.},
}

2. DOI link: , or

3. Using citation information from CITATION.CFF file.

• Set subplot sizes by default: automate setting off and offy.
• Compatibility of seaborn plots with polar layout.
• Layering the interval vizualizations on the polar layout.
• Connection styles.
• Other features and improvements.

• https://github.com/moshi4/pyCirclize
• https://github.com/ponnhide/pyCircos

Annotations.

annot_labels(
    ax_chrom: Axes,
    data: DataFrame,
    colx: str,
    chrom_y: float,
    col_label: str,
    loc: str = 'out',
    col_start: str = None,
    ax: Axes = None,
    coly: str = None,
    col_labelx: str = 'label x',
    color: str = 'darkgray',
    yoff_scales: float = None,
    off_labels_segments: float = 20,
    scale_polar: float = 1.5,
    fig: Figure = None,
    test: bool = False
) → Axes

Annot labels e.g. gene names

Args:

• ax_chrom (plt.Axes): subplot with the chromosome plot
• col_label (str): column with the labels
• loc (str, optional): locations. Defaults to 'out'.
• color (str, optional): color. Defaults to 'darkgray'.
• yoff_scales (float, optional): y offset. Defaults to None.
• off_labels_segments (float, optional): offset for the label segments. Defaults to 20.
• scale_polar (float, optional): scale for the polar plot. Defaults to 1.5.
• fig (plt.Figure, optional): figure. Defaults to None.
• test (bool, optional): test-mode. Defaults to False.

Returns:

• plt.Axes: subplot

show_segments(
    ax: Axes,
    y: float,
    offy: float,
    kind: str = 'arrows',
    segments: dict = None,
    segments_kws: dict = {},
    offytext: float = 0.2,
    arrow_kws: dict = {'color': 'k', 'lw': 1, 'alpha': 1, 'arrowstyle': '<->'},
    test: bool = False,
    **kws_annotate
) → Axes

Show segments aligned to chromosome arm.

Args:

• ax (plt.Axes): subplot
• data (pd.DataFrame): input data
• size (int): size of the segments

Chromosome plots

to_polar(
    a: list,
    range1: list = None,
    range2: list = None,
    interval: int = None
) → list

To polar coordinates

Args:

• a (list): Coordinates
• range1 (list, optional): range1. Defaults to None.
• range2 (list, optional): range2. Defaults to None.
• interval (int, optional): interval size. Defaults to None.

Raises:

• ValueError: Coordinates format

Returns:

• list: rescaled coordinates

plot_arm(
    data: DataFrame,
    arc: bool = False,
    col_start: str = 'start',
    col_end: str = 'end',
    y: float = 0,
    lw: float = 10,
    ec: str = 'k',
    pi_span: float = 1,
    pi_start: int = 0,
    pi_end: int = None,
    polar_smoothness_scale: float = 1,
    kws_pre_xys: dict = None,
    figsize: list = None,
    ax: Axes = None,
    test: bool = False,
    solid_capstyle='round'
) → Axes

Plot chromosome arm.

Args:

• data (pd.DataFrame): input table.
• y (float, optional): y position. Defaults to 0.
• lw (float, optional): line width. Defaults to 20.
• ec (str, optional): edge color. Defaults to 'k'.
• ax (plt.Axes, optional): subplot. Defaults to None.
• test (bool, optional): test-mode. Defaults to False.

Returns:

• plt.Axes: subplot

plot_chrom(
    data: DataFrame,
    arc: bool = False,
    col_start: str = 'start',
    col_end: str = 'end',
    col_arm: str = 'arm',
    pi_span: float = 1,
    pi_start: int = 0,
    pi_end: int = None,
    ax: Axes = None,
    figsize: list = None,
    **kws_plot_arm
) → Axes

Plot a chromosome

Args:

• data (pd.DataFrame): cytobands
• arc (bool, optional): arc/polar mode. Defaults to False.
• col_start (str, optional): column with start positions. Defaults to 'start'.
• col_end (str, optional): column with end positions. Defaults to 'end'.
• col_arm (str, optional): column with arm names. Defaults to 'arm'.
• pi_span (float, optional): pi span. Defaults to 1.
• pi_start (int, optional): pi start. Defaults to 0.
• pi_end (int, optional): pi end. Defaults to None.
• ax (plt.Axes, optional): subplot. Defaults to None.
• figsize (list, optional): sigure size. Defaults to None.

Returns:

• plt.Axes: subplot

plot_chroms(
    data: DataFrame,
    arc=True,
    chromosomes: list = None,
    col_start='start',
    col_end='end',
    col_arm='arm',
    span_color: str = '#dcdcdc',
    span_color_alpha_scale: float = 1,
    pi_span: float = 1,
    pi_start: int = 0,
    pi_end: int = None,
    show_labels: bool = True,
    show_vline: bool = True,
    label_y: str = None,
    test: bool = False,
    ax: Axes = None,
    figsize: list = None,
    out_data: bool = False,
    **kws_plot_arm
)

Plot chromosomes joined.

Args:

• data (pd.DataFrame): cytonbands
• arc (bool, optional): arc/polar mode. Defaults to True.
• chromosomes (list, optional): chromosomes. Defaults to None.
• col_start (str, optional): column with start position. Defaults to 'start'.
• col_end (str, optional): column with end position. Defaults to 'end'.
• col_arm (str, optional): column with chromosome arm names. Defaults to 'arm'.
• span_color (str, optional): span color. Defaults to 'whitesmoke'.
• span_color_alpha_scale (float, optional): span color transparency scale. Defaults to 1.
• pi_span (float, optional): pi span. Defaults to 1.
• pi_start (int, optional): pi start angle. Defaults to 0.
• pi_end (int, optional): pi end angle. Defaults to None.
• show_labels (bool, optional): show labels. Defaults to True.
• show_vline (bool, optional): show vertical line. Defaults to True.
• label_y (str, optional): label y. Defaults to None.
• test (bool, optional): test-mode. Defaults to False.
• ax (plt.Axes, optional): subplot. Defaults to None.
• figsize (list, optional): figure size. Defaults to None.
• out_data (bool, optional): output data. Defaults to False.

annot_chroms(
    data: DataFrame,
    chromosomes: list,
    ax_chrom: Axes = None,
    chrom_y: float = 0,
    kws_add_ax: dict = {},
    test: bool = False,
    **kws_plot
) → Axes

Add a subplot with the chromosome.

Args:

• data (pd.DataFrame): table with cytobands
• chromosomes (list): chromosomes
• ax_chrom (plt.Axes, optional): subplot with chromosome plot. Defaults to None.
• chrom_y (float, optional): chromosome y-position. Defaults to 0.
• kws_add_ax (dict, optional): keyword parameters provided to _add_ax. Defaults to {}.
• test (bool, optional): test mode. Defaults to False.

Returns:

• plt.Axes: subplot

plot_with_chroms(
    data: DataFrame,
    cytobands: DataFrame,
    kind: str,
    colx: str,
    coly: str,
    col_label: str,
    va: str,
    col_start: str = None,
    xkind: str = 'loci',
    coffy: str = None,
    off: float = None,
    offy: float = None,
    chrom_y: float = 0,
    arc: bool = True,
    pi_span: float = 1,
    pi_start: int = 0,
    pi_end: int = None,
    fig: Figure = None,
    figsize: list = None,
    ax_data: Axes = None,
    kws_seaborn: dict = {},
    kws_annot_chroms: dict = {},
    kws_annot_labels: dict = {},
    test: bool = False
) → Figure

Plot with chromosomes.

Args:

• data (pd.DataFrame): input table
• cytobands (pd.DataFrame): cytobands
• kind (str): kind of plot
• colx (str): column with x values
• coly (str): column with y values
• col_label (str): column with labels
• va (str): vertical alignment
• col_start (str, optional): column with start positions. Defaults to None.
• xkind (str, optional): kind of x values. Defaults to 'loci'.
• off (float, optional): offset scale of the chromosome plot. Defaults to None.
• offy (float, optional): offset y of the chromosome plot. Defaults to None.
• chrom_y (float, optional): chromosome y-position. Defaults to 0.
• arc (bool, optional): arc/polar plot or linear/rectangular one. Defaults to True.
• pi_span (float, optional): pi span. Defaults to 1.
• pi_start (int, optional): pi start. Defaults to 0.
• pi_end (int, optional): pi end. Defaults to None.
• fig (plt.Figure, optional): figure. Defaults to None.
• figsize (list, optional): figure size. Defaults to None.
• ax_data (plt.Axes, optional): subplot with the data plot. Defaults to None.
• kws_seaborn (dict, optional): keyword parameters to seaborn plot. Defaults to {}.
• kws_annot_chroms (dict, optional): keyword parameters to the chromosome plot. Defaults to {}.
• kws_annot_labels (dict, optional): keyword parameters to the annotations of the labels. Defaults to {}.
• test (bool, optional): test mode. Defaults to False.

Returns:

• plt.Figure: figure

plot_seaborn(
    data: DataFrame,
    kind: str,
    colx: str,
    coly: str,
    range1_chroms: list,
    arc: bool = True,
    pi_span: float = 1,
    pi_start: int = 0,
    pi_end: int = None,
    figsize: list = None,
    ax: Axes = None,
    fig: Figure = None,
    **kws_plot
) → tuple

plot_seaborn summary

Args:

• data (pd.DataFrame): input data
• kind (str): kind of plot, seaborn function name
• coly (str): column with y values
• range1_chroms (list): input range of chromosomes
• arc (bool, optional): arc/polar or linear/rectangular plots. Defaults to True.
• pi_span (float, optional): pi span. Defaults to 1.
• pi_start (int, optional): pi start position. Defaults to 0.
• pi_end (int, optional): pi end position. Defaults to None.
• figsize (list, optional): figure size. Defaults to None.
• ax (plt.Axes, optional): subplot. Defaults to None.
• fig (plt.Figure, optional): figure. Defaults to None.

Returns:

• tuple: subplot and data

TODOs: 1. set rlabel position.

heatmaps_strips(
    data: DataFrame,
    strips_kws: dict,
    fig: Figure = None,
    axs: list = None,
    kws_subplots: list = {}
) → tuple

Plot heatmap strips

Args:

• data (pd.DataFrame): input data
• strips_kws (dict): keyword arguments provided to strips
• fig (plt.Figure, optional): figure. Defaults to None.
• axs (list, optional): subplots. Defaults to None.
• kws_subplots (list, optional): keyword arguments provided to subplots. Defaults to {}.

Returns:

• tuple: figure and subplots

plot_ranges(
    data: DataFrame,
    col_id: str,
    col_start: str,
    col_end: str,
    end: int,
    start: int = 0,
    hue: str = None,
    y=None,
    kind=None,
    cytobands: dict = None,
    cytobands_y: float = None,
    col_groupby: str = None,
    col_label: str = None,
    colors: dict = None,
    lw: int = 10,
    zorders: dict = None,
    show_segments: bool = False,
    xtick_interval: float = None,
    test: bool = False,
    ax: Axes = None
) → Axes

Plot ranges.

Args:

• data (pd.DataFrame): input data.
• col_id (str): column with ids.
• col_start (str): column with start co-ordinates.
• col_end (str): column with end co-ordinates.
• end (int): end position for the plot
• start (int, optional): start position for the plot. Defaults to 0.
• hue (str, optional): column with color. Defaults to None.
• y (type, optional): column with y positions. Defaults to None.
• cytobands (dict, optional): cytobands to plot the chromosomes. Defaults to None.
• cytobands_y (float, optional): cytobands y-position. Defaults to None.
• col_groupby (str, optional): column to group by. Defaults to None.
• col_label (str, optional): column with labels. Defaults to None.
• colors (dict, optional): colors. Defaults to None.
• lw (int, optional): line width. Defaults to 10.
• zorders (dict, optional): z-orders. Defaults to None.
• show_segments (bool, optional): show segments. Defaults to False.
• xtick_interval (float, optional): x tick intervals. Defaults to None.
• test (bool, optional): test-mode. Defaults to False.
• ax (plt.Axes, optional): subplot. Defaults to None.

Raises:

• ValueError: if kind is not 'split','separate' or 'joined'

Returns:

• plt.Axes: subplot