The success of genome-wide association studies (GWASs) has led to increasing interest in making predictions of complex trait phenotypes, including disease, from genotype data. Rigorous assessment of the value of predictors is crucial before implementation. Here we discuss some of the limitations and pitfalls of prediction analysis and show how naive implementations can lead to severe bias and misinterpretation of results
Empirical studies suggest that the effect sizes of individual causal risk alleles underlying complex...
Background: There is increasing interest in investigating genetic risk models in empirical studies, ...
BackgroundThe prediction of the genetic disease risk of an individual is a powerful public health to...
Genomic prediction has the potential to contribute to precision medicine. However, to date, the util...
Genomic prediction has the potential to contribute to precision medicine. However, to date, the util...
Reliable risk assessment of frequent, but treatable diseases and disorders has considerable clinical...
Compared to univariate analysis of genome-wide association (GWA) studies, machine learning–...
Genomic prediction has the potential to contribute to precision medicine. However, to date, the util...
Genome-wide association studies have helped us identify a wealth of genetic variants associated with...
Recent advances in genome-wide association studies have stimulated interest in the genomic predictio...
Background - The prediction of the genetic disease risk of an individual is a powerful public health...
Motivation: Using simulation studies for quantitative trait loci, we evaluate the prediction quality...
Complex diseases are often highly heritable. However, for many complex traits only a small proportio...
Genome-wide association studies (GWA) try to identify the genetic polymorphisms associated with vari...
Genome-wide association studies (GWAS) have provided valuable insights into the genetic basis of com...
Empirical studies suggest that the effect sizes of individual causal risk alleles underlying complex...
Background: There is increasing interest in investigating genetic risk models in empirical studies, ...
BackgroundThe prediction of the genetic disease risk of an individual is a powerful public health to...
Genomic prediction has the potential to contribute to precision medicine. However, to date, the util...
Genomic prediction has the potential to contribute to precision medicine. However, to date, the util...
Reliable risk assessment of frequent, but treatable diseases and disorders has considerable clinical...
Compared to univariate analysis of genome-wide association (GWA) studies, machine learning–...
Genomic prediction has the potential to contribute to precision medicine. However, to date, the util...
Genome-wide association studies have helped us identify a wealth of genetic variants associated with...
Recent advances in genome-wide association studies have stimulated interest in the genomic predictio...
Background - The prediction of the genetic disease risk of an individual is a powerful public health...
Motivation: Using simulation studies for quantitative trait loci, we evaluate the prediction quality...
Complex diseases are often highly heritable. However, for many complex traits only a small proportio...
Genome-wide association studies (GWA) try to identify the genetic polymorphisms associated with vari...
Genome-wide association studies (GWAS) have provided valuable insights into the genetic basis of com...
Empirical studies suggest that the effect sizes of individual causal risk alleles underlying complex...
Background: There is increasing interest in investigating genetic risk models in empirical studies, ...
BackgroundThe prediction of the genetic disease risk of an individual is a powerful public health to...