ArticleBMC bioinformatics2025
BiomiX, a user-friendly bioinformatic tool for democratized analysis and integration of multiomics data.
Article in BMC bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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
6 citing papers in PubMed.
- Assessing current capabilities for incorporating lipidomics in multiomics data integration.Briefings in bioinformatics · 2026Review
- Accelerating genetic gain through integrated genomic selection in crop plants.Journal of applied genetics · 2026Review
- The crosstalk between epigenetics and metabolism in the malignant cell.Discover oncology · 2026Review
- Article
- Prompt-based bioinformatics: a new interface for multi-omics analysis.Nature reviews. Genetics · 2025Article
- Multi-omics decodes host-specific and environmental microbiome interactions in sepsis.Frontiers in microbiology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
backgroundInterpreting biological system changes requires interpreting vast amounts of multi-omics data. While user-friendly tools exist for single-omics analysis, integrating multiple omics still requires bioinformatics expertise, limiting accessibility for the broader scientific community.
resultsBiomiX tackles the bottleneck in high-throughput omics data analysis, enabling efficient and integrated analysis of multiomics data obtained from two cohorts. BiomiX incorporates diverse omics data, using DESeq2/Limma packages for transcriptomics, and quantifying metabolomics peak differences, evaluated via the Wilcoxon test with the False Discovery Rate correction. The metabolomics annotation for Liquid Chromatography-Mass Spectrometry untargeted metabolomics is additionally supported using the mass-to-charge ratio in the CEU Mass Mediator database and fragmentation spectra in the TidyMass package. Methylomics analysis is performed using the ChAMP R package. Finally, Multi-Omics Factor Analysis (MOFA) integration identifies shared sources of variation across omics data. BiomiX also generates statistics, report figures and integrates EnrichR and GSEA for biological process exploration and subgroup analysis based on user-defined gene panels enhancing condition subtyping. BiomiX fine-tunes MOFA models, to optimize factors number selection, distinguishing between cohorts and providing tools to interpret discriminative MOFA factors. The interpretation relies on innovative bibliography research on Pubmed, which provides the articles most related to the discriminant factor contributors. Furthermore, discriminant MOFA factors are correlated with clinical data, and the top contributing pathways are explored, all with the aim of guiding the user in factor interpretation.
conclusionsThe analysis of single-omics and multi-omics integration in a standalone tool, along with MOFA implementation and its interpretability via literature, represents significant progress in the multi-omics field in line with the "Findable, Accessible, Interoperable, and Reusable" data principles. BiomiX offers a wide range of parameters and interactive data visualization, allowing for personalized analysis tailored to user needs. This R-based, user-friendly tool is compatible with multiple operating systems and aims to make multi-omics analysis accessible to non-experts in bioinformatics.
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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.