MOTIVATION: Accurate disease risk prediction is an essential step in the modern quest for precision medicine. While high-dimensional multi-omics data have provided unprecedented data resources for prediction studies, their high-dimensionality and complex inter/intra-relationships have posed significant analytical challenges. RESULTS: We proposed a two-step Bayesian linear mixed model framework (TBLMM) for risk prediction analysis on multi-omics data. TBLMM models the predictive effects from multi-omics data using a hybrid of the sparsity regression and linear mixed model with multiple random effects. It can resemble the shape of the true effect size distributions and accounts for non-linear, including interaction effects, among multi-omics data via kernel fusion. It infers its parameters via a computationally efficient variational Bayes algorithm. Through extensive simulation studies and the prediction analyses on the positron emission tomography imaging outcomes using data obtained from the Alzheimer's Disease Neuroimaging Initiative, we have demonstrated that TBLMM can consistently outperform the existing method in predicting the risk of complex traits. AVAILABILITY AND IMPLEMENTATION: The corresponding R package is available on GitHub (https://github.com/YaluWen/TBLMM).

Azimuth multichannel synthetic aperture radar(SAR) is a form of SAR with one transmitter and several receivers, which is able to obtain both high resolution and wide swath imaging. Azimuth spectrum reconstruction is core operation in the data processing of azimuth multichannel SAR. The spatial variation of Doppler center frequency is non-ignorable in multichannel SAR of squint view, meanwhile, in sliding spotlight SAR imaging mode, the Doppler spectrum of the signal increases greatly due to the rotation of the beam direction, thus, the traditional reconstruction algorithm fails to reconstruct the signal spectrum correctly. To solve above problems, an improved azimuth spectrum reconstruction and imaging processing algorithm for squint multichannel SAR in sliding spotlight mode is proposed. By analyzing the characteristics of multichannel signals in two-dimensional frequency domain, a new spectrum reconstruction matrix is established. Besides, by combining the Deramp operation with the reconstruction algorithm, the Doppler bandwidth caused by the rotation of the beam center is removed. Finally, imaging algorithm of single channel SAR is used to image the reconstructed signal. Simulation experiments verify the effectiveness of the method.