sumstatlib

gwascatalog.sumstatlib

This library contains Pydantic models for new types of genetic variation stored in the GWAS Catalog ("beyond SNPs").

It doesn't provide any user facing applications. Its purpose is to contain validation and domain logic for summary statistic validation applications (gwascatalog.sumstatapp).

Developer notes

Data model overview

This library contains Pydantic models which support validating Gene-based GWAS and Copy Number Variant (CNV) GWAS. In the future new types of data might be validated (e.g. SNPs).

classDiagram
    direction TB

    class BaseSumstatModel {
        <<abstract>>

        %% configuration (conceptual)
        +p_value : PValue | None
        +neg_log10_p_value : NegLog10pValue | None

        +z_score : ZScore | None
        +odds_ratio : OddsRatio | None
        +beta : Beta | None
        +hazard_ratio : HazardRatio | None
        +standard_error : StandardError | None

        +confidence_interval_lower : ConfidenceIntervalLower | None
        +confidence_interval_upper : ConfidenceIntervalUpper | None

        +n : SampleSizePerVariant | None

        --
        -_primary_effect_size : Literal["beta","z_score","hazard_ratio","odds_ratio"] | None

        -_allow_zero_pvalues : bool
    }

    class CNVSumstatModel {
        <<final>>

        +MIN_RECORDS : int
        +FIELD_MAP : Mapping[str,int]
        +VALID_FIELD_NAMES : list[str]

        +chromosome : Chromosome
        +base_pair_start : BasePairStart
        +base_pair_end : BasePairEnd
        +statistical_model_type : StatisticalModelTypeField

        --
        -_assembly : GenomeAssembly
    }

    class GeneSumstatModel {
        <<final>>

        +MIN_RECORDS : int
        +FIELD_MAP : Mapping[str,int]
        +VALID_FIELD_NAMES : list[str]

        +ensembl_gene_id : EnsemblGeneID | None
        +hgnc_symbol : HGNCGeneSymbol | None

        +chromosome : Chromosome | None
        +base_pair_start : BasePairStart | None
        +base_pair_end : BasePairEnd | None
    }

    BaseSumstatModel <|-- GeneSumstatModel
    BaseSumstatModel <|-- CNVSumstatModel

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Implementing a new data model

If you want to implement a new data model you should:

1. Create a new Python package inside src/gwascatalog/sumstatlib
2. Set up annotated types for each field in the new model, importing and reusing types from the core package where possible
3. Compose a new data model from the annotated types, inheriting from the abstract BaseSumstatModel class
4. Add tests for your new types and model
5. Add your model to __all__ in the library's root __init__.py