malariagen_data.af1.Af1.plot_ihs_gwss

Af1.plot_ihs_gwss(contig: str, analysis: str = 'default', sample_sets: Sequence[str] | str | None = None, sample_query: str | None = None, sample_query_options: dict | None = None, window_size: int = 200, percentiles: int | Tuple[int, ...] = (50, 75, 100), standardize: bool = True, standardization_bins: Tuple[float, ...] | None = None, standardization_n_bins: int = 20, standardization_diagnostics: bool = False, filter_min_maf: float = 0.05, compute_min_maf: float = 0.05, min_ehh: float = 0.05, max_gap: int = 200000, gap_scale: int = 20000, include_edges: bool = True, use_threads: bool = True, min_cohort_size: int | None = 15, max_cohort_size: int | None = 50, random_seed: int = 42, palette: str = 'Blues', title: str | bool | None = None, sizing_mode: Literal['fixed', 'stretch_width', 'stretch_height', 'stretch_both', 'scale_width', 'scale_height', 'scale_both'] = 'stretch_width', width: int | None = None, track_height: int = 170, genes_height: int = 90, show: bool = True, output_backend: Literal['canvas', 'webgl', 'svg'] = 'webgl', chunks: int | str | Tuple[int | str, ...] | Callable[[Tuple[int, ...]], int | str | Tuple[int | str, ...]] = 'native', inline_array: bool = True, gene_labels: Mapping[str, str] | None = None, gene_labelset: LabelSet | None = None) → Model | None

Run and plot iHS GWSS data.

Parameters

contigstr

Reference genome contig name. See the contigs property for valid contig names.

analysisstr, optional, default: ‘default’

Which haplotype phasing analysis to use. See the phasing_analysis_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.

window_sizeint, optional, default: 200

The size of window in number of SNPs used to summarise iHS over. If None, per-variant iHS values are returned.

percentilesint or tuple of int, optional, default: (50, 75, 100)

If window size is specified, this returns the iHS percentiles for each window.

standardizebool, optional, default: True

If True, standardize iHS values by alternate allele counts.

standardization_binstuple of float or None, optional

If provided, use these allele count bins to standardize iHS values.

standardization_n_binsint, optional, default: 20

Number of allele count bins to use for standardization. Overrides standardization_bins.

standardization_diagnosticsbool, optional, default: False

If True, plot some diagnostics about the standardization.

filter_min_maffloat, optional, default: 0.05

Minimum minor allele frequency to use for filtering prior to passing haplotypes to allel.ihs function.

compute_min_maffloat, optional, default: 0.05

Do not compute integrated haplotype homozygosity for variants with minor allele frequency below this threshold.

min_ehhfloat, optional, default: 0.05

Minimum EHH beyond which to truncate integrated haplotype homozygosity calculation.

max_gapint, optional, default: 200000

Do not report scores if EHH spans a gap larger than this number of base pairs.

gap_scaleint, optional, default: 20000

Rescale distance between variants if gap is larger than this value.

include_edgesbool, optional, default: True

If True, report scores even if EHH does not decay below min_ehh at the end of the chromosome.

use_threadsbool, optional, default: True

If True, use multiple threads to compute iHS.

min_cohort_sizeint or None, optional, default: 15

Minimum cohort size. Raise an error if the number of samples is less than this value.

max_cohort_sizeint or None, optional, default: 50

Randomly down-sample to this value if the number of samples in the cohort is greater.

random_seedint, optional, default: 42

Random seed used for reproducible down-sampling.

palettestr, optional, default: ‘Blues’

Name of bokeh palette to use for plotting multiple percentiles.

titlestr or bool or None, optional

Plot title. If True, a title may be automatically generated.

sizing_mode{‘fixed’, ‘stretch_width’, ‘stretch_height’, ‘stretch_both’, ‘scale_width’, ‘scale_height’, ‘scale_both’}, optional, default: ‘stretch_width’

Bokeh plot sizing mode, see also https://docs.bokeh.org/en/latest/docs /user_guide/basic/layouts.html#sizing-modes.

widthint or None, optional

Plot width in pixels (px).

track_heightint, optional, default: 170

Main track height in pixels (px).

genes_heightint, optional, default: 90

Genes track height in pixels (px).

showbool, optional, default: True

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

output_backend{‘canvas’, ‘webgl’, ‘svg’}, optional, default: ‘webgl’

Specify an output backend to render a plot area onto. See also https://docs.bokeh.org/en/latest/docs/user_guide/output/webgl.html.

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().

gene_labelsMapping[str, str] or None, optional

A mapping of gene identifiers to custom labels, which will appear in the plot.

gene_labelsetLabelSet or None, optional

A LabelSet to use in the plot.

Returns

Model or None

A bokeh figure (only returned if show=False).