ReviewFrontiers in bioinformatics2022
Applications and Comparison of Dimensionality Reduction Methods for Microbiome Data.
Review in Frontiers in bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- Review
- Higher-dimensional ordination analysis teases out impacts ofMicrobiology spectrum · 2026Article
- Multidimensional scaling informed by F-statistic: Visualizing grouped microbiome data with inference.PLoS computational biology · 2026Article
- Microbiota-host interaction in colorectal cancer: emerging computational technology, multi-omics integration, and mechanisms.Cancer biology & medicine · 2026Review
- Predicted meta-omics: A potential solution to multi-omics data scarcity in microbiome studies.PloS one · 2026Article
- Signatures of local nitrogen adaptation in the Brachypodium distachyon root microbiome.The New phytologist · 2026Article
- Predicting oil contamination in water using machine learning on microbial compositions.PloS one · 2026Article
- Data-driven enterosignatures link gut microbiome reorganization to heat stress responses in lactating sows.Frontiers in microbiology · 2026Article
- Artificial Intelligence-Driven Food Safety: Decoding Gut Microbiota-Mediated Health Effects of Non-Microbial Contaminants.Foods (Basel, Switzerland) · 2025Review
- A foundation model for microbial growth dynamics.bioRxiv : the preprint server for biology · 2025Article
- Mouse strain-specific responses along the gut-brain axis upon fecal microbiota transplantation from children with autism.Gut microbes · 2025Article
- Review
- Linear Dimensionality Reduction Methods for Analyzing Structured Biomedical Data: Existing Research and Future Opportunities.Wiley interdisciplinary reviews. Computational statistics · 2025Review
- Do we need a standardized 16S rRNA gene amplicon sequencing analysis protocol for poultry microbiota research?Poultry science · 2025Review
- Linear scaling reveals low-dimensional structure in observable microbial dynamics.bioRxiv : the preprint server for biology · 2025Article
- Article
- Multidimensional scaling improves distance-based clustering for microbiome data.Bioinformatics (Oxford, England) · 2025Article
- amplysis: an R package for microbial composition and diversity analysis using 16S rRNA amplicon data.Briefings in functional genomics · 2025Article
- Effects of data transformation and model selection on feature importance in microbiome classification data.Microbiome · 2025Article
- A benchmark analysis of feature selection and machine learning methods for environmental metabarcoding datasets.Computational and structural biotechnology journal · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Dimensionality reduction techniques are a key component of most microbiome studies, providing both the ability to tractably visualize complex microbiome datasets and the starting point for additional, more formal, statistical analyses. In this review, we discuss the motivation for applying dimensionality reduction techniques, the special characteristics of microbiome data such as sparsity and compositionality that make this difficult, the different categories of strategies that are available for dimensionality reduction, and examples from the literature of how they have been successfully applied (together with pitfalls to avoid). We conclude by describing the need for further development in the field, in particular combining the power of phylogenetic analysis with the ability to handle sparsity, compositionality, and non-normality, as well as discussing current techniques that should be applied more widely in future analyses.
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