ArticleCommunications for statistical applications and methods2022
A guideline for the statistical analysis of compositional data in immunology.
Article in Communications for statistical applications and methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Decoding the cancer microbiome: multi-omics, AI, and translational opportunities.Genome biology · 2026Review
- Associations of accelerometry-derived time in major activity intensities with cognitive outcomes: a compositional data analysis approach.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026Article
- Differences in immune cell profiles around the time of islet autoimmunity seroconversion in children with and without type 1 diabetes.BMJ open diabetes research & care · 2026Article
- Compositional maturation of the microbiome and adaptive immunity in the postnatal period.Frontiers in immunology · 2026Article
- Personalized, disease-stage specific, rapid identification of immunosuppression in sepsis.Frontiers in immunology · 2024Article
- DNA methylation profiles reveal sex-specific associations between gestational exposure to ambient air pollution and placenta cell-type composition in the PRISM cohort study.Clinical epigenetics · 2023Article
- Pre-treatment inflamed tumor immune microenvironment is associated with FOLFIRINOX response in pancreatic cancer.Frontiers in oncology · 2023Article
- Three approaches to supervised learning for compositional data with pairwise logratios.Journal of applied statistics · 2023Article
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Authors and funding
6 authors.
Funding
Abstract
The study of immune cellular composition has been of great scientific interest in immunology because of the generation of multiple large-scale data. From the statistical point of view, such immune cellular data should be treated as compositional. In compositional data, each element is positive, and all the elements sum to a constant, which can be set to one in general. Standard statistical methods are not directly applicable for the analysis of compositional data because they do not appropriately handle correlations between the compositional elements. In this paper, we review statistical methods for compositional data analysis and illustrate them in the context of immunology. Specifically, we focus on regression analyses using log-ratio transformations and the alternative approach using Dirichlet regression analysis, discuss their theoretical foundations, and illustrate their applications with immune cellular fraction data generated from colorectal cancer patients.
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