panukb_meta_analysis_high_quality

Schema (0.3, GRCh37)

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Global fields:
    None
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Column fields:
    'trait_type': str
    'phenocode': str
    'pheno_sex': str
    'coding': str
    'modifier': str
    'pheno_data': array<struct {
        n_cases: int32,
        n_controls: int32,
        heritability: struct {
            estimates: struct {
                ldsc: struct {
                    h2_liability: float64,
                    h2_liability_se: float64,
                    h2_z: float64,
                    h2_observed: float64,
                    h2_observed_se: float64,
                    intercept: float64,
                    intercept_se: float64,
                    ratio: float64,
                    ratio_se: float64
                },
                sldsc_25bin: struct {
                    h2_liability: float64,
                    h2_liability_se: float64,
                    h2_z: float64,
                    h2_observed: float64,
                    h2_observed_se: float64,
                    intercept: float64,
                    intercept_se: float64,
                    ratio: float64,
                    ratio_se: float64
                },
                rhemc_25bin: struct {
                    h2_liability: float64,
                    h2_liability_se: float64,
                    h2_z: float64,
                    h2_observed: float64,
                    h2_observed_se: float64
                },
                rhemc_8bin: struct {
                    h2_liability: float64,
                    h2_liability_se: float64,
                    h2_observed: float64,
                    h2_observed_se: float64,
                    h2_z: float64
                },
                rhemc_25bin_50rv: struct {
                    h2_observed: float64,
                    h2_observed_se: float64,
                    h2_liability: float64,
                    h2_liability_se: float64,
                    h2_z: float64
                },
                final: struct {
                    h2_observed: float64,
                    h2_observed_se: float64,
                    h2_liability: float64,
                    h2_liability_se: float64,
                    h2_z: float64
                }
            },
            qcflags: struct {
                GWAS_run: bool,
                ancestry_reasonable_n: bool,
                defined_h2: bool,
                significant_z: bool,
                in_bounds_h2: bool,
                normal_lambda: bool,
                normal_ratio: bool,
                EUR_plus_1: bool,
                pass_all: bool
            },
            N_ancestry_QC_pass: int32
        },
        saige_version: str,
        inv_normalized: bool,
        pop: str,
        lambda_gc: float64,
        n_variants: int64,
        n_sig_variants: int64,
        saige_heritability: float64
    }>
    'description': str
    'description_more': str
    'coding_description': str
    'category': str
    'n_cases_full_cohort_both_sexes': int64
    'n_cases_full_cohort_females': int64
    'n_cases_full_cohort_males': int64
    'meta_analysis_data': array<struct {
        n_cases: int32,
        n_controls: int32,
        pop: array<str>
    }>
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Row fields:
    'locus': locus<GRCh37>
    'alleles': array<str>
    'rsid': str
    'varid': str
    'vep': struct {
        assembly_name: str,
        allele_string: str,
        ancestral: str,
        colocated_variants: array<struct {
            aa_allele: str,
            aa_maf: float64,
            afr_allele: str,
            afr_maf: float64,
            allele_string: str,
            amr_allele: str,
            amr_maf: float64,
            clin_sig: array<str>,
            end: int32,
            eas_allele: str,
            eas_maf: float64,
            ea_allele: str,
            ea_maf: float64,
            eur_allele: str,
            eur_maf: float64,
            exac_adj_allele: str,
            exac_adj_maf: float64,
            exac_allele: str,
            exac_afr_allele: str,
            exac_afr_maf: float64,
            exac_amr_allele: str,
            exac_amr_maf: float64,
            exac_eas_allele: str,
            exac_eas_maf: float64,
            exac_fin_allele: str,
            exac_fin_maf: float64,
            exac_maf: float64,
            exac_nfe_allele: str,
            exac_nfe_maf: float64,
            exac_oth_allele: str,
            exac_oth_maf: float64,
            exac_sas_allele: str,
            exac_sas_maf: float64,
            id: str,
            minor_allele: str,
            minor_allele_freq: float64,
            phenotype_or_disease: int32,
            pubmed: array<int32>,
            sas_allele: str,
            sas_maf: float64,
            somatic: int32,
            start: int32,
            strand: int32
        }>,
        context: str,
        end: int32,
        id: str,
        input: str,
        intergenic_consequences: array<struct {
            allele_num: int32,
            consequence_terms: array<str>,
            impact: str,
            minimised: int32,
            variant_allele: str
        }>,
        most_severe_consequence: str,
        motif_feature_consequences: array<struct {
            allele_num: int32,
            consequence_terms: array<str>,
            high_inf_pos: str,
            impact: str,
            minimised: int32,
            motif_feature_id: str,
            motif_name: str,
            motif_pos: int32,
            motif_score_change: float64,
            strand: int32,
            variant_allele: str
        }>,
        regulatory_feature_consequences: array<struct {
            allele_num: int32,
            biotype: str,
            consequence_terms: array<str>,
            impact: str,
            minimised: int32,
            regulatory_feature_id: str,
            variant_allele: str
        }>,
        seq_region_name: str,
        start: int32,
        strand: int32,
        transcript_consequences: array<struct {
            allele_num: int32,
            amino_acids: str,
            biotype: str,
            canonical: int32,
            ccds: str,
            cdna_start: int32,
            cdna_end: int32,
            cds_end: int32,
            cds_start: int32,
            codons: str,
            consequence_terms: array<str>,
            distance: int32,
            domains: array<struct {
                db: str,
                name: str
            }>,
            exon: str,
            gene_id: str,
            gene_pheno: int32,
            gene_symbol: str,
            gene_symbol_source: str,
            hgnc_id: str,
            hgvsc: str,
            hgvsp: str,
            hgvs_offset: int32,
            impact: str,
            intron: str,
            lof: str,
            lof_flags: str,
            lof_filter: str,
            lof_info: str,
            minimised: int32,
            polyphen_prediction: str,
            polyphen_score: float64,
            protein_end: int32,
            protein_start: int32,
            protein_id: str,
            sift_prediction: str,
            sift_score: float64,
            strand: int32,
            swissprot: str,
            transcript_id: str,
            trembl: str,
            uniparc: str,
            variant_allele: str
        }>,
        variant_class: str
    }
    'freq': array<struct {
        pop: str,
        ac: float64,
        af: float64,
        an: int64,
        gnomad_exomes_ac: int32,
        gnomad_exomes_af: float64,
        gnomad_exomes_an: int32,
        gnomad_genomes_ac: int32,
        gnomad_genomes_af: float64,
        gnomad_genomes_an: int32
    }>
    'pass_gnomad_exomes': bool
    'pass_gnomad_genomes': bool
    'n_passing_populations': int32
    'high_quality': bool
    'nearest_genes': str
    'info': float64
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Entry fields:
    'meta_analysis': array<struct {
        BETA: float64,
        SE: float64,
        Pvalue: float64,
        Q: float64,
        Pvalue_het: float64,
        N: int32,
        N_pops: int32,
        AF_Allele2: float64,
        AF_Cases: float64,
        AF_Controls: float64
    }>
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Column key: ['trait_type', 'phenocode', 'pheno_sex', 'coding', 'modifier']
Row key: ['locus', 'alleles']
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