Many statistical machine approaches could ultimately highlight novel features of the etiology of complex diseases by analyzing multi-omics data. However, they are sensitive to some deviations in distribution when the observed samples are potentially contaminated with adversarial corrupted outliers (e.g., a fictional data distribution). Likewise, statistical advances lag in supporting comprehensive data-driven analyses of complex multi-omics data integration. We propose a novel non-linear M-estimator-based approach, "robust kernel machine regression (RobKMR)," to improve the robustness of statistical machine regression and the diversity of fictional data to examine the higher-order composite effect of multi-omics datasets. We address a robust kernel-centered Gram matrix to estimate the model parameters accurately. We also propose a robust score test to assess the marginal and joint Hadamard product of features from multi-omics data. We apply our proposed approach to a multi-omics dataset of osteoporosis (OP) from Caucasian females. Experiments demonstrate that the proposed approach effectively identifies the inter-related risk factors of OP. With solid evidence (p-value = 0.00001), biological validations, network-based analysis, causal inference, and drug repurposing, the selected three triplets ((DKK1, SMTN, DRGX), (MTND5, FASTKD2, CSMD3), (MTND5, COG3, CSMD3)) are significant biomarkers and directly relate to BMD. Overall, the top three selected genes (DKK1, MTND5, FASTKD2) and one gene (SIDT1 at p-value= 0.001) significantly bond with four drugs- Tacrolimus, Ibandronate, Alendronate, and Bazedoxifene out of 30 candidates for drug repurposing in OP. Further, the proposed approach can be applied to any disease model where multi-omics datasets are available.
翻译:许多统计机方法最终可以通过分析多组类集数据来突出复杂疾病病理学的新特征;然而,当观测到的样本可能受到对抗性腐蚀的离子体污染(例如虚构的数据分布);同样,统计进步在支持对复杂的多组类集数据整合进行全面数据驱动分析方面滞后;我们建议采用新的非线性M-测量法,“罗布斯内核机回归(RobKMRMR)”,以提高统计机回归的稳健性和虚构数据的多样性,以检查多组组群数据集的更高层次混合效应。 我们还建议采用强力的评分测试,以评估多组集成数据集成的边际和联合的哈马特产品;我们建议采用B-Omical-内核回归(RODMRMR), 白种雌性(OD-MFMRMD),3,S-MFMR-MRMD 3, IMF-MD 3, IMF-ML 3,IMF-ML3,IMF-MD IMD 3,IMF-MD IMD,O,IMF-MD3,O,O,O,O,O,O,O-MFMD3,O,O,O,O,O-MFMD3,O,O-MFMD,O,O,O,O-MD,O,O,O,O,O,O,O,O,O,O,O,O,O,OD,O,O,O,OD,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,OD,OD,OD,OD,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,O,