ArticleGenome biology2025
Incorporating scale uncertainty in microbiome and gene expression analysis as an extension of normalization.
Article in Genome biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Article
- Not every gene is special: Modelling scale controls the false discovery rate when analysing high-throughput sequencing data.PLoS computational biology · 2026Article
- Internal-External Heterogeneity in Downed Logs Across Decay Stages: Divergent Wood Chemistry and Contrasting Bacterial and Fungal Responses.Microorganisms · 2026Article
- From diversity to dominance: how salt and CO₂ shape LAB-dominated ecosystems in vegetable fermentations.Microbiology spectrum · 2026Article
- Scale reliant mixed effects models enhance microbiome data analysis.Microbiome · 2026Article
- Comprehensive evaluation of statistical approaches for differential metaproteomics.bioRxiv : the preprint server for biology · 2026Article
- Article
- Metagenome analysis of Citrus sinensis rhizosphere infected with Candidatus liberibacter asiaticus reveals distinct structure in bacterial communities.Scientific reports · 2025Article
- Uncertainty Modeling Outperforms Machine Learning for Microbiome Data Analysis.bioRxiv : the preprint server for biology · 2025Article
- Explicit Scale Simulation for analysis of RNA-sequencing count data with ALDEx2.NAR genomics and bioinformatics · 2025Article
- Brain-wide connectivity and novelty response of the dorsal endopiriform nucleus in mice.Cell reports · 2025Article
- Replacing normalizations with interval assumptions enhances differential expression and differential abundance analyses.BMC bioinformatics · 2025Article
- Incorporating scale uncertainty in microbiome and gene expression analysis as an extension of normalization.Genome biology · 2025Article
- Compositional transformations can reasonably introduce phenotype-associated values into sparse features.mSystems · 2025Article
- Scalable Inference for Bayesian Multinomial Logistic-Normal Dynamic Linear Models.Proceedings of machine learning research · 2025Article
- Compositional data analysis enables statistical rigor in comparative glycomics.Nature communications · 2025Article
- Compositional transformations can reasonably introduce phenotype-associated values into sparse features.bioRxiv : the preprint server for biology · 2025Article
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3 authors.
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Abstract
Statistical normalizations are used in differential analyses to address sample-to-sample variation in sequencing depth. Yet normalizations make strong, implicit assumptions about the scale of biological systems, such as microbial load, leading to false positives and negatives. We introduce scale models as a generalization of normalizations, which allows researchers to model potential errors in these modeling assumptions, thereby enhancing the transparency and robustness of data analyses. In practice, scale models can drastically reduce false positives and false negatives rates. We introduce updates to the popular ALDEx2 software package, available on Bioconductor, facilitating scale model analysis.
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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.