Motivation: Genome-wide association studies (GWASs) have identified many genetic loci associated with complex traits. A substantial fraction of these identified loci are associated with multiple traits -a phenomena known as pleiotropy. Identification of pleiotropic associations can help characterize the genetic relationship among complex traits and can facilitate our understanding of disease etiology. Effective pleiotropic association mapping requires the development of statistical methods that can jointly model multiple traits with genome-wide SNPs together.Results: We develop a joint modeling method, which we refer to as the integrative MApping of Pleiotropic association (iMAP). iMAP models summary statistics from GWASs, uses a multivariate Gaussian distribution to account for phenotypic correlation, simultaneously infers genome-wide SNP association pattern using mixture modeling, and has the potential to reveal causal relationship between traits. Importantly, iMAP integrates a large number of SNP functional annotations to substantially improve association mapping power, and, with a sparsity-inducing penalty, is capable of selecting informative annotations from a large, potentially noninformative set. To enable scalable inference of iMAP to association studies with hundreds of thousands of individuals and millions of SNPs, we develop an efficient expectation maximization not peer-reviewed)

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To quantify the oscillation characteristics of wind power systems, the stator dynamics of the induction generators is included. An interface including the stator voltage angle is given, changing the network parameter to the dq frame, which proves that the stator dynamics can not be ignored for practical systems with limited synchronous capacity. But the stator parameters can not be chosen as the state variables. The steady-state and dynamic stability models are derived with the proposed interface. It is found that the instable modes in wind power systems do not satisfy the electromechanical loop participation ratio, and can not be classified as the interarea modes among the synchronous generators. The participation factors shows the dependency of the oscillations on the induction generators, which is validated by the time-domain analysis. The dynamic response of the synchronous generators and the loads further validates that the oscillations are close to voltage oscillation instead of angular instability.

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