在生物信息学中会用到这样一个方法:Joint and Individual Variation Explained。在仅介绍方法推论部分,实际案例可直接阅读文献。不足之处请指导。 文献:JIVE 方法在卵巢癌多组学数据整合分析中的应用 背景介绍: 使用TCGA 数据库中卵巢癌miRNA 和 miRNA 的组学数据,应用 JIVE 方法整合分析两个组学数据,提取两不同组学...
In this paper we\nintroduce Angle-Based Joint and Individual Variation Explained capturing both\njoint and individual variation within each data block. This is a major\nimprovement over earlier approaches to this challenge in terms of a new\nconceptual understanding, much better adaption to data ...
(intNMF)17, Joint and Individual Variation Explained (JIVE)18, Multiple co-inertia analysis (MCIA)19, Multi-Omics Factor Analysis (MOFA)15, Multi-Study Factor Analysis (MSFA)20, Regularized Generalized Canonical Correlation Analysis (RGCCA)21, matrix-tri-factorization (scikit-fusion)22, and ...
B. Joint and individual variation explained (JIVE) for integrated analysis of multiple data types. Ann. Appl. Stat. 7, 523–542 (2013). Article PubMed PubMed Central Google Scholar Argelaguet, R. et al. Multi‐omics factor analysis—a framework for unsupervised integration of multi‐omics ...
The rationale for the choice of strategy in situations with conflicting player preferences was explained in Table 4a, Table 4b. The expected oil reserves owned by player A are larger than those owned by player B. As a consequence, there will be a higher probability for sA = 2 than sB = ...
11. What is the clinical relationship between abdominal (visceral) obesity, blood lipid levels, and metabolic syndrome? 12. What is the effect of dietary intake on the clinical lipid profile and blood lipoprotein levels? 13. What is the effect of physical activity on the clinical lipid profile...
A naïve approach would be to consider PSA as a time-dependent variable in an extended Cox/relative risk model [27]. However, this is not appropriate due to the endogenous nature of the biomarker of interest [28,29], which contains biological variation and measurement error. A further exten...
resulting in individual inputs instead ofgroup consensus. Also, if numerous users are involved, it becomes infeasible to conduct all these interviews, both from time and resource perspectives. These challenges led to the emergence of JAD, where group consensus matters more than individual inputs or...
Single-cell and single-nucleus RNA-sequencing (sxRNA-seq) is increasingly being used to characterise the transcriptomic state of cell types at homeostasis, during development and in disease. However, this is a challenging task, as biological effects can be masked by technical variation. Here, we...
The 30 lead SNPs combined explained 1.03% to 1.83% of variation among the 15 cranial vault segments, and 1.31% of global cranial vault shape variation after adjustment for covariates. We observed a range of associated phenotypic effects, with some GWAS signals impacting multiple regions of the ...