malariagen_data.af1.Af1.fst_gwss

Af1.fst_gwss(contig: str, window_size: int, cohort1_query: str, cohort2_query: str, sample_query_options: dict | None = None, sample_sets: Sequence[str] | str | None = None, site_mask: str | None = 'default', cohort_size: int | None = None, min_cohort_size: int | None = 15, max_cohort_size: int | None = 50, random_seed: int = 42, inline_array: bool = True, chunks: int | str | Tuple[int | str, ...] | Callable[[Tuple[int, ...]], int | str | Tuple[int | str, ...]] = 'native', clip_min: float | None = 0.0) → Tuple[ndarray, ndarray]

Run a Fst genome-wide scan to investigate genetic differentiation between two cohorts.

Parameters

contigstr

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

window_sizeint

The size of windows (number of sites) used to calculate statistics within.

cohort1_querystr

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

cohort2_querystr

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.

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.

site_maskstr or None, optional, default: ‘default’

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

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.

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.

inline_arraybool, optional, default: True

Passed through to dask from_array().

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.

clip_minfloat or None, optional, default: 0.0

Minimum value for Fst. Values below this are clipped to this value.

Returns

xndarray

An array containing the window centre point genomic positions.

fstndarray

An array with Fst statistic values for each window.