Article

Identifying novel associations in GWAS by hierarchical Bayesian latent variable detection of differentially misclassified phenotypes

2019-01-31

Abstract excerpt

Heterogeneity in definition and measurement of complex diseases in Genome-Wide Association Studies (GWAS) may lead to misdiagnoses and misclassification errors that can significantly impact discovery of disease loci. While well appreciated, almost all analyses of GWAS data consider reported disease phenotype values as is without accounting for potential misclassification. Here, we introduce Phenotype Latent variab...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: fc38a11a-bdc3-587f-aef8-a1fd24fa6d7a
DOI: 10.1101/536532

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Identifying novel associations in GWAS by hierarchical Bayesian latent variable detection of differentially misclassified phenotypesDOI 10.1101/536532Read

Identifying novel associations in GWAS by hierarchical Bayesian latent variable detection of differentially misclassified phenotypes.Semantic proximity Read

Reducing misclassification bias in electronic health record-based GWAS of psychiatric traits using the SuperControl frameworkSemantic proximity Read

Incorporating phenotype heterogeneity in disease GWAS improves power while maintaining specificitySemantic proximity Read

Detecting and Adjusting for Hidden Biases due to Phenotype Misclassification in Genome-Wide Association StudiesSemantic proximity Read

Efficient penalized generalized linear mixed models for variable selection and genetic risk prediction in high-dimensional data.Semantic proximity Read

Reclassification of genetic-based risk predictions as GWAS data accumulate.Semantic proximity Read

Bayesian analysis of genetic association across tree-structured routine healthcare data in the UK BiobankSemantic proximity Read

Incorporating scientific knowledge into phenotype development: penalized latent class regression.Semantic proximity Read

Estimating missing heritability for disease from genome-wide association studies.Semantic proximity Read

Leveraging correlations between polygenic risk score predictors to detect heterogeneity in GWAS cohortsSemantic proximity Read

Leveraging correlations between variants in polygenic risk scores to detect heterogeneity in GWAS cohorts.Semantic proximity Read

Improving the power of genetic association tests with imperfect phenotype derived from electronic medical records.Semantic proximity Read