Estimating heritability and genetic correlations from large health datasets in the absence of genetic data
Typically, estimating genetic parameters, such as disease heritability and between-disease
genetic correlations, demands large datasets containing all relevant phenotypic measures
and detailed knowledge of family relationships or, alternatively, genotypic and phenotypic
data for numerous unrelated individuals. Here, we suggest an alternative, efficient
estimation approach through the construction of two disease metrics from large health
datasets: temporal disease prevalence curves and low-dimensional disease embeddings …
genetic correlations, demands large datasets containing all relevant phenotypic measures
and detailed knowledge of family relationships or, alternatively, genotypic and phenotypic
data for numerous unrelated individuals. Here, we suggest an alternative, efficient
estimation approach through the construction of two disease metrics from large health
datasets: temporal disease prevalence curves and low-dimensional disease embeddings …
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