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updates to genetic ancestry analysis
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@smgogarten
smgogarten committed Jun 26, 2024
1 parent c37d4e2 commit 5ef5626
Showing 1 changed file with 173 additions and 12 deletions.
185 changes: 173 additions & 12 deletions PRIMED_GSR_data_model.json
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},
{
"column": "dbsnp_build_version",
"description": "dbSNP build for the rsIDS included in GSR files",
"description": "dbSNP build for the rsIDs included in GSR files",
"data_type": "string"
},
{
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"data_type": "string",
"multi_value_delimiter": "|",
"examples": "a60fb66cd539ad2c",
"notes": "From Genotype data model: array_dataset_id, imputation_dataset_id, or sequencing_dataset_id"
"notes": "From PRIMED inventory workspace"
},
{
"column": "analysis_workspace_id",
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"description": "email of the PRIMED contributor who can be contacted for data related questions",
"data_type": "string",
"notes": "recommended by WG. helpful when GSR is not publicly released and is from a Biobank or some other source"
},
{
"column": "reference_assembly",
"required": true,
"description": "Reference genome assembly that the submitted data is mapped to",
"data_type": "enumeration",
"enumerations": ["GRCh38", "GRCh37", "NCBI36", "NCBI35", "NCBI34"],
"examples": "GRCh38"
},
{
"column": "dbsnp_build_version",
"description": "dbSNP build for the rsIDs included in GSR files",
"data_type": "string"
},
{
"column": "n_variants",
"required": true,
"description": "Total number of variants in the analysis results across all chromosomes",
"data_type": "integer",
"examples": "1000000",
"notes": "This will be used for a QC step to check data integrity of submitted data"
},
{
"column": "min_MAF_filter",
"description": "minimum minor allele frequency filter",
"data_type": "float",
"examples": "0.01"
},
{
"column": "min_MAC_filter",
"description": "minimum minor allele count filter",
"data_type": "integer",
"examples": "20"
},
{
"column": "LD_max_r2_filter",
"description": "maximum r^2 for SNPs kept in LD pruning",
"data_type": "float",
"examples": "0.1"
},
{
"column": "genotyping_technology",
"required": true,
"description": "The genotyping technology used for detecting variants",
"data_type": "enumeration",
"enumerations": ["genome-wide array", "WGS", "exome array", "WES", "other array"],
"multi_value_delimiter": "|"
},
{
"column": "genotyping_platform",
"required": true,
"description": "Genotyping platform description including manufacturer, array name, sequencer name",
"data_type": "string",
"multi_value_delimiter": "|",
"examples": ["Illumina GSA", "Illumina Omni-2.5", "Illumina HiSeq", "Affymetrix"],
"notes": "put 'unavailable' if unknown"
},
{
"column": "is_imputed",
"required": true,
"description": "Indicator of whether the analysis was performed using imputed genotypes or dosages",
"data_type": "boolean",
"enumerations": ["TRUE", "FALSE"],
"examples": true
},
{
"column": "imputation_reference_panel",
"required": "CONDITIONAL (is_imputed = TRUE)",
"description": "Reference panel use for imputation",
"data_type": "enumeration",
"enumerations": ["1000 Genomes", "HRC", "TOPMed", "Other"],
"examples": "TOPMed",
"notes": "Put 'Other' if not one of the common reference panels listed. Can include further information in imputation_reference_panel_detail or README"
},
{
"column": "imputation_reference_panel_detail",
"required": "CONDITIONAL (is_imputed = TRUE)",
"description": "Details of the imputation reference panel; e.g. version number or name of panel when imputation_reference_panel = 'Other'",
"data_type": "string",
"examples": "TOPMed r2",
"notes": "version number or name of 'other' include N/A"
},
{
"column": "imputation_quality_filter",
"required": "CONDITIONAL (is_imputed = TRUE)",
"description": "minimum imputation quality value (e.g. Rsq, info) for filtering imputed variants",
"data_type": "float",
"examples": "0.3",
"notes": "If no filter, enter value of 0"
},
{
"column": "n_samp",
"required": true,
"description": "Total sample size in the analysis",
"data_type": "integer",
"notes": "When different markers have different sample sizes, e.g, due to missing genotypes, use max sample size across markers"
},
{
"column": "cohorts",
"required": true,
"description": "A list of cohorts that collected the samples.",
"data_type": "string",
"multi_value_delimiter": "|"
},
{
"column": "population_descriptor",
"required": true,
"description": "the concept or classification scheme used to categorize people into populations for this analysis",
"data_type": "string",
"examples": "reported ancestry"
},
{
"column": "population_labels",
"required": true,
"description": "name given to a population that describes or classifies it according to the dimension along which it was identified",
"data_type": "string",
"multi_value_delimiter": "|",
"examples": "Chinese Americans | European Americans | African Americans"
},
{
"column": "population_proportions",
"description": "proportion of participants from each population in the same order mapping to the values in the population_labels variable",
"data_type": "string",
"multi_value_delimiter": "|",
"examples": "0.7 | 0.1 | 0.2"
},
{
"column": "countries_of_recruitment",
"required": true,
"description": "Reported countries of recruitment",
"data_type": "string",
"multi_value_delimiter": "|",
"examples": "Ghana | Kenya | Nigeria"
},
{
"column": "countries_of_birth",
"description": "Reported countries of birth",
"data_type": "string",
"multi_value_delimiter": "|",
"examples": "Ghana | Kenya | Nigeria"
},
{
"column": "analysis_method",
"required": true,
"description": "The name or description of the method or computational algorithm used for genetic ancestry analysis.",
"data_type": "string",
"multi_value_delimiter": "|",
"examples": ["linear regression", "logistic regression", "LMM", "GLMM", "meta-analysis"]
},
{
"column": "analysis_software",
"description": "The name of the software used for the genetic anestry analysis",
"data_type": "string",
"multi_value_delimiter": "|",
"examples": ["GCTA", "PLINK", "GENESIS", "SAIGE"]
},
{
"column": "primed_dataset_id",
"description": "For analyses that used a dataset in primed individual data model indicate its dataset_id",
"data_type": "string",
"multi_value_delimiter": "|",
"examples": "a60fb66cd539ad2c",
"notes": "From PRIMED inventory workspace"
},
{
"column": "analysis_workspace_id",
"description": "workspace identifier for the GWAS that was generated in PRIMED",
"data_type": "string",
"examples": "primed-analysis/PRIMED_ANALYSIS_GERA-topmed-v3-imputation"
}
]
},
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"required": true,
"description": "Type of the file",
"data_type": "string",
"examples": ["SNP loadings", "PCs", "admixture proportions"]
"examples": ["SNP loadings", "allele frequencies"]
},
{
"column": "n_variants",
"description": "Count of variants in the GSR data file",
"data_type": "integer",
"examples": "15281216",
"notes": "If applicable (e.g. SNP loading files)"
},
{
"column": "n_samp",
"description": "Count of samples in the GSR data file",
"data_type": "integer",
"examples": "4500",
"notes": "If applicable (e.g. individual-level PC files)"
"examples": "15281216"
}
]
}
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