quantify their contribution to the inflation of test statistics in GWAS. In this communication, we extend the LD Score regression approach by applying the generalized estimation equations (GEE) framework, which is capable of incorporating more external information from reference panels about the correlation structure of test statistics. We apply our GEE approach and LD Score regression to simul...

Genome-wide association studies (GWAS) have been the focus of considerable effort in psychiatry. These efforts have markedly increased knowledge of the genetic basis of psychiatric disorders, and yielded empirical data on genetic architecture critical to addressing long-standing debates in the field. There is a now a clear path to increased knowledge of the 'parts lists' for these disorders.

Heritability estimates of general intelligence in adulthood generally range from 75 to 85%, with all heritability due to additive genetic influences, while genetic dominance and shared environmental factors are absent, or too small to be detected. These estimates are derived from studies based on the classical twin design and are based on the assumption of random mating. Yet, considerable posit...

Genome-wide association studies (GWAS) identify genetic variants that distinguish a control population from a population with a specific trait. Two challenges in GWAS are: (1) identification of the causal variant within a longer haplotype that is associated with the trait; (2) identification of causal variants for polygenic traits that are caused by variants in multiple genes within a pathway. ...

OBJECTIVE Predictive tests that capitalize on emerging genetic findings hold great promise for enhanced personalized healthcare. With the emergence of a large amount of data from genome-wide association studies (GWAS), interest has shifted towards high-dimensional risk prediction. METHODS To form predictive genetic tests on high-dimensional data, we propose a non-parametric method, called the...

Genetic epidemiologists strive to determine the genetic profile of diseases. Epistasis is the interaction between two or more genes to affect phenotype. Due to the often non-linearity of the interaction, it is difficult to detect statistical patterns of epistasis. Combinatorial methods for detecting epistasis investigate a subset of combinations of genes without employing a search strategy. The...

Apart from the specific findings of this analysis, the authors encourage the use of what they call a nutrientwide association study, analogous to a genome-wide association study (GWAS), to investigate dietary determinants of health outcomes.1 Similar to the agnostic approach used in a GWAS, the features of their approach include the following: (1) the inclusion of all available nutrient exposur...

In recent years pleiotropy, the phenomenon of one genetic locus influencing several traits, has become a widely researched field in human genetics. With the increasing availability of genome-wide association study summary statistics, as well as the establishment of deeply phenotyped sample collections, it is now possible to systematically assess the genetic overlap between multiple traits and d...

2 Conducting GWAS with genphen 2 2.1 Input . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.2 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.2.1 runGenphenRf and runGenphenSvm . . . . . . . . . . 3 2.2.2 runGenphenBayes . . . . . . . . . . . . . . . . . . . . 5 2.3 Case studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.3.1 SNP-phenot...

Most individuals throughout the Americas are admixed descendants of Native American, European, and African ancestors. Complex historical factors have resulted in varying proportions of ancestral contributions between individuals within and among ethnic groups. We developed a panel of 446 ancestry informative markers (AIMs) optimized to estimate ancestral proportions in individuals and populatio...