ArticleBMC bioinformatics2019
Vertical and horizontal integration of multi-omics data with miodin.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
34 citing papers in PubMed.
- Review
- A cooperative learning framework for the integration of metabolomic data from multiple cohorts and common phenotype identification.Computational and structural biotechnology journal · 2026Article
- Harnessing Multi-Omics and Predictive Modeling for Climate-Resilient Crop Breeding: From Genomes to Fields.Genes · 2025Review
- Defined culture conditions robustly maintain human stem cell pluripotency, highlighting a role for CaCommunications biology · 2025Article
- Wise Roles and Future Visionary Endeavors of Current Emperor: Advancing Dynamic Methods for Longitudinal Microbiome Meta-Omics Data in Personalized and Precision Medicine.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Review
- Review
- Unfolding and de-confounding: biologically meaningful causal inference from longitudinal multi-omic networks using METALICA.mSystems · 2024Article
- Multimodal functional deep learning for multiomics data.Briefings in bioinformatics · 2024Article
- hCoCena: A toolbox for network-based co-expression analysis and horizontal integration of transcriptomic datasets.STAR protocols · 2024Article
- Methods for multi-omic data integration in cancer research.Frontiers in genetics · 2024Review
- Statistical integration of multi-omics and drug screening data from cell lines.PLoS computational biology · 2024Article
- Unfolding and De-confounding: Biologically meaningful causal inference from longitudinal multi-omic networks using METALICA.bioRxiv : the preprint server for biology · 2023Article
- The hitchhikers' guide to RNA sequencing and functional analysis.Briefings in bioinformatics · 2023Article
- Proteomics in Inherited Metabolic Disorders.International journal of molecular sciences · 2022Review
- hCoCena: horizontal integration and analysis of transcriptomics datasets.Bioinformatics (Oxford, England) · 2022Article
- Characterization of methylation patterns associated with lifestyle factors and vitamin D supplementation in a healthy elderly cohort from Southwest Sweden.Scientific reports · 2022Article
- Machine-learning algorithms based on personalized pathways for a novel predictive model for the diagnosis of hepatocellular carcinoma.BMC bioinformatics · 2022Article
- Data Mining IdentifiesLife (Basel, Switzerland) · 2022Article
- A guide for the diagnosis of rare and undiagnosed disease: beyond the exome.Genome medicine · 2022Review
- Overview of methods for characterization and visualization of a protein-protein interaction network in a multi-omics integration context.Frontiers in molecular biosciences · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
backgroundStudies on multiple modalities of omics data such as transcriptomics, genomics and proteomics are growing in popularity, since they allow us to investigate complex mechanisms across molecular layers. It is widely recognized that integrative omics analysis holds the promise to unlock novel and actionable biological insights into health and disease. Integration of multi-omics data remains challenging, however, and requires combination of several software tools and extensive technical expertise to account for the properties of heterogeneous data.
resultsThis paper presents the miodin R package, which provides a streamlined workflow-based syntax for multi-omics data analysis. The package allows users to perform analysis of omics data either across experiments on the same samples (vertical integration), or across studies on the same variables (horizontal integration). Workflows have been designed to promote transparent data analysis and reduce the technical expertise required to perform low-level data import and processing.
conclusionsThe miodin package is implemented in R and is freely available for use and extension under the GPL-3 license. Package source, reference documentation and user manual are available at https://gitlab.com/algoromics/miodin.
Indexed as
Identifiers
What OpenQuestion holds
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.