malariagen_data.af1.Af1.cnv_coverage_calls

Af1.cnv_coverage_calls(region: str | Region | Mapping | List[str | Region | Mapping] | Tuple[str | Region | Mapping, ...], sample_set: str, analysis: str, inline_array: bool = True, chunks: int | str | Tuple[int | str, ...] | Callable[[Tuple[int, ...]], int | str | Tuple[int | str, ...]] = 'native') → Dataset

Access CNV HMM data from genome-wide CNV discovery and filtering.

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.

sample_setstr

Sample set identifier.

analysisstr

Which coverage calls analysis to use. See the coverage_calls_analysis_ids property for available values.

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.

Returns

Dataset

A dataset with 2 dimensions: variants the number of CNV regions in the selected region, samples the number of samples. There are 5 coordinates: variant_position has variants values and contains the initial position of each CNV region, variant_end has variants values and contains the final position of each CNV region, variant_contig has variants values and contains the contig of each CNV region, variant_id has variants values and contains the identifier for each CNV region, sample_id has samples values and contains the identifier of each sample. It contains 4 data variables: variant_CIPOS, it has variants values and contains the confidence interval for the start position for each CNV region, variant_CIEND, it has variants values and contains the confidence interval for the end position for each CNV region, variant_filter_pass, it has variants values and is True for each CNV region that passes quality filters, call_genotype, it has (variants, samples) values and contains the coverage call for each sample and each CNV region,.