During the past decade, genome-wide association studies (GWAS) have been used to
successfully identify tens of thousands of genetic variants associated with complex traits and …

It is well known that when data are nonnormally distributed, a test of the significance of
Pearson's r may inflate Type I error rates and reduce power. Statistics textbooks and the …

Mendelian randomization, a method to infer causal relationships, is confounded by genetic
correlations reflecting shared etiology. We developed a model in which a latent causal …

Hundreds of papers and factors attempt to explain the cross-section of expected returns.
Given this extensive data mining, it does not make sense to use the usual criteria for …

The poolr package provides an implementation of a variety of methods for pooling (ie,
combining) p values, including Fisher's method, Stouffer's method, the inverse chisquare …

Standard statistical approaches for prioritization of variants for functional testing in fine-
mapping studies either use marginal association statistics or estimate posterior probabilities …

Complex traits and common diseases are extremely polygenic, their heritability spread
across thousands of loci. One possible explanation is that thousands of genes and loci have …

Integrating single nucleotide polymorphism (SNP) p-values from genome-wide association
studies (GWAS) across genes and pathways is a strategy to improve statistical power and …

Current genome-wide association studies (GWAS) use commercial genotyping microarrays
that can assay over a million single nucleotide polymorphisms (SNPs). The number of SNPs …

BACKGROUND: Osteoarthritis is the most common form of arthritis worldwide and is a major
cause of pain and disability in elderly people. The health economic burden of osteoarthritis …