ArticleWiley interdisciplinary reviews. Computational statistics
Integrative Analysis of "-Omics" Data Using Penalty Functions.
Article in Wiley interdisciplinary reviews. Computational statistics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Integrative rank-based regression for multi-source high-dimensional data with multi-type responses.Journal of applied statistics · 2025Article
- Heterogeneity-aware integrative regression for ancestry-specific association studies.Biometrics · 2024Article
- Binned multinomial logistic regression for integrative cell-type annotation.The annals of applied statistics · 2023Article
- Prior information-assisted integrative analysis of multiple datasets.Bioinformatics (Oxford, England) · 2023Article
- Integrative Learning of Structured High-Dimensional Data from Multiple Datasets.Statistical analysis and data mining · 2023Article
- Heterogeneous data integration methods for patient similarity networks.Briefings in bioinformatics · 2022Review
- Vertical integration methods for gene expression data analysis.Briefings in bioinformatics · 2021Review
- Integrative sparse partial least squares.Statistics in medicine · 2021Article
- Meta-Analyzing Multiple Omics Data With Robust Variable Selection.Frontiers in genetics · 2021Article
- An integrative sparse boosting analysis of cancer genomic commonality and difference.Statistical methods in medical research · 2020Article
- Integrating approximate single factor graphical models.Statistics in medicine · 2020Article
- Multiset sparse partial least squares path modeling for high dimensional omics data analysis.BMC bioinformatics · 2020Article
- GRIA: Graphical Regularization for Integrative Analysis.Proceedings of the ... SIAM International Conference on Data Mining. SIAM International Conference on Data Mining · 2020Article
- Horizontal and vertical integrative analysis methods for mental disorders omics data.Scientific reports · 2019Article
- Identifying gene-environment interactions incorporating prior information.Statistics in medicine · 2019Article
- A Selective Review of Multi-Level Omics Data Integration Using Variable Selection.High-throughput · 2019Review
- Integrative sparse principal component analysis of gene expression data.Genetic epidemiology · 2017Article
- Accommodating missingness in environmental measurements in gene-environment interaction analysis.Genetic epidemiology · 2017Article
- Article
- Promoting Similarity of Sparsity Structures in Integrative Analysis with Penalization.Journal of the American Statistical Association · 2017Article
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Authors and funding
6 authors.
Funding
Abstract
In the analysis of omics data, integrative analysis provides an effective way of pooling information across multiple datasets or multiple correlated responses, and can be more effective than single-dataset (response) analysis. Multiple families of integrative analysis methods have been proposed in the literature. The current review focuses on the penalization methods. Special attention is paid to sparse meta-analysis methods that pool summary statistics across datasets, and integrative analysis methods that pool raw data across datasets. We discuss their formulation and rationale. Beyond "standard" penalized selection, we also review contrasted penalization and Laplacian penalization which accommodate finer data structures. The computational aspects, including computational algorithms and tuning parameter selection, are examined. This review concludes with possible limitations and extensions.
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