Multitrait Analysis to Decipher the Intertwined Genetic Architecture of Neuroanatomical Phenotypes and Psychiatric Disorders.

Background: There is increasing evidence of shared genetic factors between psychiatric disorders and brain magnetic resonance imaging (MRI) phenotypes. However, deciphering the joint genetic architecture of these outcomes has proven to be challenging, and new approaches are needed to infer the genetic structures that may underlie those phenotypes. Multivariate analyses are a meaningful approach to reveal links between MRI phenotypes and psychiatric disorders missed by univariate approaches.

Trait selection strategy in multi-trait GWAS: Boosting SNP discoverability.

Since the first genome-wide association studies (GWASs), thousands of variant-trait associations have been discovered. However, comprehensively mapping the genetic determinant of complex traits through univariate testing can require prohibitive sample sizes. Multi-trait GWAS can circumvent this issue and improve statistical power by leveraging the joint genetic architecture of human phenotypes.

MANOCCA: a robust and computationally efficient test of covariance in high-dimension multivariate omics data.

Multivariate analysis is becoming central in studies investigating high-throughput molecular data, yet, some important features of these data are seldom explored. Here, we present MANOCCA (Multivariate Analysis of Conditional CovAriance), a powerful method to test for the effect of a predictor on the covariance matrix of a multivariate outcome. The proposed test is by construction orthogonal to tests based on the mean and variance and is able to capture effects that are missed by both approaches.

Trait selection strategy in multi-trait GWAS: Boosting SNPs discoverability.

Since the first Genome-Wide Association Studies (GWAS), thousands of variant-trait associations have been discovered. However, the sample size required to detect additional variants using standard univariate association screening is increasingly prohibitive. Multi-trait GWAS offers a relevant alternative: it can improve statistical power and lead to new insights about gene function and the joint genetic architecture of human phenotypes.

Effects of substituting yellow corn for sorghum in geese diets on magret and foie gras quality.

The aim of this trial was to study the effects of substitution of yellow corn with sorghum during the growing-finishing (G period), overfeeding (O period), or both periods on magret and foie gras quality in geese. In total, 260 ganders were divided into 4 groups (65 birds in each) differing in the cereal (yellow corn or sorghum) included in the diet given during the G and the O periods, using a 2 × 2 factorial arrangement of treatments. The groups differed in the nature of the cereal in the diet offered to birds between 44 and 104 d of age (G period: a diet containing 500 g of sorghum/kg (SS and SC groups) or a diet containing 500 g of yellow corn/kg (CS and CC groups).