malariagen_data.ag3.Ag3.plot_diplotype_clustering#

Ag3.plot_diplotype_clustering(region: str | Region | Mapping | List[str | Region | Mapping] | Tuple[str | Region | Mapping, ...], site_mask: str | None = 'default', sample_sets: Sequence[str] | str | None = None, sample_query: str | None = None, sample_query_options: dict | None = None, cohort_size: int | None = None, random_seed: int = 42, color: str | Mapping | None = None, symbol: str | Mapping | None = None, linkage_method: Literal['single', 'complete', 'average', 'weighted', 'centroid', 'median', 'ward'] = 'complete', distance_metric: Literal['cityblock', 'euclidean', 'sqeuclidean'] = 'cityblock', count_sort: bool | None = None, distance_sort: bool | None = None, title: str | bool | None = True, title_font_size: int = 14, width: int | None = None, height: int | None = 500, show: bool = True, renderer: str | None = None, render_mode: Literal['auto', 'svg', 'webgl'] = 'svg', leaf_y: int = 0, marker_size: int | float = 5, line_width: int | float = 0.5, line_color: str = 'black', color_discrete_sequence: List | None = None, color_discrete_map: Mapping | None = None, category_orders: List | Mapping | None = None, legend_sizing: Literal['constant', 'trace'] = 'constant', chunks: int | str | Tuple[int | str, ...] | Callable[[Tuple[int, ...]], int | str | Tuple[int | str, ...]] = 'native', inline_array: bool = True) dict | None#

Hierarchically cluster diplotypes in region and produce an interactive plot.

Parameters#

regionstr or Region or Mapping or list of str or Region or Mapping or tuple of str or Region or Mapping

Region of the reference genome. Can be a contig name, region string (formatted like “{contig}:{start}-{end}”), or identifier of a genome feature such as a gene or transcript. Can also be a sequence (e.g., list) of regions.

site_maskstr or None, optional, default: ‘default’

Which site filters mask to apply. See the site_mask_ids property for available values.

sample_setssequence of str or str or None, optional

List of sample sets and/or releases. Can also be a single sample set or release.

sample_querystr or None, optional

A pandas query string to be evaluated against the sample metadata, to select samples to be included in the returned data.

sample_query_optionsdict or None, optional

A dictionary of arguments that will be passed through to pandas query() or eval(), e.g. parser, engine, local_dict, global_dict, resolvers.

cohort_sizeint or None, optional

Randomly down-sample to this value if the number of samples in the cohort is greater. Raise an error if the number of samples is less than this value.

random_seedint, optional, default: 42

Random seed used for reproducible down-sampling.

colorstr or Mapping or None, optional

Name of variable to use to color the markers.

symbolstr or Mapping or None, optional

Name of the variable to use to choose marker symbols.

linkage_method{‘single’, ‘complete’, ‘average’, ‘weighted’, ‘centroid’, ‘median’, ‘ward’}, optional, default: ‘complete’

The linkage algorithm to use. See the Linkage Methods section of the scipy.cluster.hierarchy.linkage docs for full descriptions.

distance_metric{‘cityblock’, ‘euclidean’, ‘sqeuclidean’}, optional, default: ‘cityblock’

The metric to compute distance between genotypes in two samples.

count_sortbool or None, optional

If True, for each node n, the child with the minimum number of descendants is plotted first. Note distance_sort and count_sort cannot both be True.

distance_sortbool or None, optional

If True, for each node n, if True, the child with the minimum distance between is plotted first. Note distance_sort and count_sort cannot both be True.

titlestr or bool or None, optional, default: True

If True, attempt to use metadata from input dataset as a plot title. Otherwise, use supplied value as a title.

title_font_sizeint, optional, default: 14

Font size for the plot title.

widthint or None, optional

Figure width in pixels (px).

heightint or None, optional, default: 500

Figure height in pixels (px).

showbool, optional, default: True

If true, show the plot. If False, do not show the plot, but return the figure.

rendererstr or None, optional

The name of the renderer to use.

render_mode{‘auto’, ‘svg’, ‘webgl’}, optional, default: ‘svg’

The type of rendering backend to use. See also https://plotly.com/python/webgl-vs-svg/.

leaf_yint, optional, default: 0

Y coordinate at which to plot the leaf markers.

marker_sizeint or float, optional, default: 5

Marker size.

line_widthint or float, optional, default: 0.5

Line width.

line_colorstr, optional, default: ‘black’

Line color.

color_discrete_sequenceList or None, optional

Provide a list of colours to use.

color_discrete_mapMapping or None, optional

Provide an explicit mapping from values to colours.

category_ordersList or Mapping or None, optional

Control the order in which values appear in the legend.

legend_sizing{‘constant’, ‘trace’}, optional, default: ‘constant’

Determines if the legend items symbols scale with their corresponding “trace” attributes or remain “constant” independent of the symbol size on the graph.

chunksint or str or tuple of int or str or Callable[[typing.Tuple[int, …]], int or str or tuple of int or str], optional, default: ‘native’

Define how input data being read from zarr should be divided into chunks for a dask computation. If ‘native’, use underlying zarr chunks. If a string specifying a target memory size, e.g., ‘300 MiB’, resize chunks in arrays with more than one dimension to match this size. If ‘auto’, let dask decide chunk size. If ‘ndauto’, let dask decide chunk size but only for arrays with more than one dimension. If ‘ndauto0’, as ‘ndauto’ but only vary the first chunk dimension. If ‘ndauto1’, as ‘ndauto’ but only vary the second chunk dimension. If ‘ndauto01’, as ‘ndauto’ but only vary the first and second chunk dimensions. Also, can be a tuple of integers, or a callable which accepts the native chunks as a single argument and returns a valid dask chunks value.

inline_arraybool, optional, default: True

Passed through to dask from_array().

Returns#

dict or None