Sentence examples for multivariate phenotypes based from inspiring English sources

Lange et al. [37] has proposed a natural extension of the FBAT statistics which are based on the general likelihood-score test approach [38] to multivariate phenotypes based on GEE scores.

Our work emphasize that multivariate phenotypes based GWAS can identify pleiotropic genes that share common etiology pathways.

We applied to multivariate phenotype based GWAS to relations between plasma lipid levels for an in-depth study.

The multivariate model we developed characterizes a "healthy aging" phenotype based upon an integration of measures that together reflect multiple dimensions of an aging adult 65-699 years of age).

My research has centered on multivariate image based phenotyping, with a focus on neurological conditions like Alzheimer's disease.

Results: Here we present a new method, multivariate gene-based association test by extended Simes procedure (MGAS), that allows gene-based testing of multivariate phenotypes in unrelated individuals.

We propose the concept of cryptotype to describe latent, multivariate phenotypes that maximize the separation of a priori classes.

We describe the model in the context of multivariate phenotypes, although we consider only bivariate situation in our analysis.

Classic multivariate methods such as likelihood based mixed effects model [ 18, 19] and generalize estimating equations (GEE) [ 20], and extended versions of these methods [ 21, 22] can be applied to multivariate phenotypes of GWAS.

In this study, we propose multivariate GMDR, an extension of GMDR for multivariate phenotypes.

Our multivariate GMDR analysis was developed by utilizing a GEE approach to multivariate phenotypes.