丁香实验_LOGO
登录
提问
我要登录
|免费注册
点赞
收藏
wx-share
分享

Mixed Effects Structural Equation Models and Phenotypic Causal Networks

互联网

325
Complex networks with causal relationships among variables are pervasive in biology. Their study, however, requires special modeling approaches. Structural equation models (SEM) allow the representation of causal mechanisms among phenotypic traits and inferring the magnitude of causal relationships. This information is important not only in understanding how variables relate to each other in a biological system, but also to predict how this system reacts under external interventions which are common in fields related to health and food production. Nevertheless, fitting a SEM requires defining a priori the causal structure among traits, which is the qualitative information that describes how traits are causally related to each other. Here, we present directions for the applications of SEM to investigate a system of phenotypic traits after searching for causal structures among them. The search may be performed under confounding effects exerted by genetic correlations.
提问
扫一扫
丁香实验小程序二维码
实验小助手
丁香实验公众号二维码
扫码领资料
反馈
TOP
打开小程序