malariagen_data.af1.Af1.biallelic_snp_calls

Af1.biallelic_snp_calls(region: str | Region | Mapping | List[str | Region | Mapping] | Tuple[str | Region | Mapping, ...], sample_sets: Sequence[str] | str | None = None, sample_query: str | None = None, sample_query_options: dict | None = None, sample_indices: List[int] | None = None, site_mask: str | None = None, site_class: str | None = None, inline_array: bool = True, chunks: int | str | Tuple[int | str, ...] | Callable[[Tuple[int, ...]], int | str | Tuple[int | str, ...]] = 'native', cohort_size: int | None = None, min_cohort_size: int | None = None, max_cohort_size: int | None = None, random_seed: int = 42, min_minor_ac: int | float | None = None, max_missing_an: int | float | None = None, n_snps: int | None = None, thin_offset: int = 0) → Dataset

Access SNP calls at sites which are biallelic within the selected samples.

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_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.

sample_indiceslist of int or None, optional

Advanced usage parameter. A list of indices of samples to select, corresponding to the order in which the samples are found within the sample metadata. Either provide this parameter or sample_query, not both.

site_maskstr or None, optional

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

site_classstr or None, optional

Select sites belonging to one of the following classes: CDS_DEG_4, (4-fold degenerate coding sites), CDS_DEG_2_SIMPLE (2-fold simple degenerate coding sites), CDS_DEG_0 (non-degenerate coding sites), INTRON_SHORT (introns shorter than 100 bp), INTRON_LONG (introns longer than 200 bp), INTRON_SPLICE_5PRIME (intron within 2 bp of 5’ splice site), INTRON_SPLICE_3PRIME (intron within 2 bp of 3’ splice site), UTR_5PRIME (5’ untranslated region), UTR_3PRIME (3’ untranslated region), INTERGENIC (intergenic, more than 10 kbp from a gene).

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.

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

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

max_cohort_sizeint or None, optional

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.

min_minor_acint or float or None, optional

The minimum minor allele count. SNPs with a minor allele count below this value will be excluded. Can also be a float, which will be interpreted as a fraction.

max_missing_anint or float or None, optional

The maximum number of missing allele calls to accept. SNPs with more than this value will be excluded. Set to 0 to require no missing calls. Can also be a float, which will be interpreted as a fraction.

n_snpsint or None, optional

The desired number of SNPs to use when running the analysis. SNPs will be evenly thinned to approximately this number.

thin_offsetint, optional, default: 0

Starting index for SNP thinning. Change this to repeat the analysis using a different set of SNPs.

Returns

Dataset

A dataset with 4 dimensions: variants: the number of sites, alleles the number of alleles (2), samples: the number of samples, ploidy: the ploidy (2). There are 3 coordinates: sample_id has samples values and contains the identifier of each sample, variant_position has variants values and contains the position of each site, variant_contig has variants values and contains the contig of each site. There are 3 data variables: variant_allele, it (variants, alleles) values and contains the nucleotide represented as a character for each site, each allele, variant_allele_count, it (variants, alleles) values and contains the number of occurences of each allele at each site, call_genotype, it (variants, samples, ploidy) values and contains and contains both calls for each site and each sample.