ArticleFrontiers in genetics2021
PathwayMultiomics: An R Package for Efficient Integrative Analysis of Multi-Omics Datasets With Matched or Un-matched Samples.
Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Cross-tissue analysis of blood and brain epigenome-wide association studies in Alzheimer's disease.Nature communications · 2022Pooled it
- Identification of key genes in chickpea transcriptomics and the development of ChickpeaOmicsR as a comprehensive resource to advance breeding and genomic studies.Frontiers in bioinformatics · 2026Article
- Brain high-throughput multi-omics data reveal molecular heterogeneity in Alzheimer's disease.PLoS biology · 2024Article
- PathIntegrate: Multivariate modelling approaches for pathway-based multi-omics data integration.PLoS computational biology · 2024Article
- PathIntegrate: Multivariate modelling approaches for pathway-based multi-omics data integration.bioRxiv : the preprint server for biology · 2024Article
- Multi-omics in stress and health research: study designs that will drive the field forward.Stress (Amsterdam, Netherlands) · 2024Review
- A comprehensive survey of the approaches for pathway analysis using multi-omics data integration.Briefings in bioinformatics · 2022Review
- The promise of multi-omics approaches to discover biological alterations with clinical relevance in Alzheimer's disease.Frontiers in aging neuroscience · 2022Review
- Applications of Omics Technology for Livestock Selection and Improvement.Frontiers in genetics · 2022Review
- Metabolic dysfunction and mitochondrial failure in Alzheimer's disease: integrating pathophysiology, clinical evidence and emerging interventions.Frontiers in neurologyReview
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Recent advances in technology have made multi-omics datasets increasingly available to researchers. To leverage the wealth of information in multi-omics data, a number of integrative analysis strategies have been proposed recently. However, effectively extracting biological insights from these large, complex datasets remains challenging. In particular, matched samples with multiple types of omics data measured on each sample are often required for multi-omics analysis tools, which can significantly reduce the sample size. Another challenge is that analysis techniques such as dimension reductions, which extract association signals in high dimensional datasets by estimating a few variables that explain most of the variations in the samples, are typically applied to whole-genome data, which can be computationally demanding. Here we present pathwayMultiomics, a pathway-based approach for integrative analysis of multi-omics data with categorical, continuous, or survival outcome variables. The input of pathwayMultiomics is pathway
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.