ReviewBioinformatics (Oxford, England)2018
Understanding sequencing data as compositions: an outlook and review.
Review in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 182 papers.
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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.
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Who cites it
182 citing papers in PubMed.
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- A New Framework to Empower Ecosystem Assessment Through the Integration of eDNA Inventories, Graph Theory and Niche Modelling.Ecology letters · 2026Article
- AI-empowered human microbiome research.Gut · 2026Review
- Egg microbiome of the yellow-spotted Amazon river turtle (Podocnemis unifilis) modulates fusariosis fungal infection and hatching success.Communications biology · 2026Article
- Comparative transcriptomics analysis of histone deacetylases, transcription factors, and ion channel genes in human iPSC-cardiomyocytes vs. the adult human heart.Journal of precision medicine (Amsterdam, Netherlands) · 2026Article
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- Chronic exposure to Salton Sea aerosols elicits pulmonary inflammation and shifts in murine lung and fecal microbiome diversity.Research square · 2026Article
- Unique nasal cell states induced by common pediatric respiratory viruses.bioRxiv : the preprint server for biology · 2026Article
- Score Matching for Differential Abundance Testing of Compositional High-Throughput Sequencing Data.Statistics in medicine · 2026Article
- Cultivation system and plant health influence root-associated bacterial community structure and interaction networks in strawberry.Scientific reports · 2026Article
- The bacteria of a fig community.Microbiology spectrum · 2026Article
- Microbiota-host interaction in colorectal cancer: emerging computational technology, multi-omics integration, and mechanisms.Cancer biology & medicine · 2026Review
- Comparison of Spatio-Temporal Dynamics and Composition in Size-Fractionated and Unfractionated Northwestern Atlantic Microbial Communities.Environmental microbiology reports · 2026Article
- Comparative transcriptomics analysis of histone deacetylases, transcription factors, and ion channel genes in human iPSC-cardiomyocytes vs. the adult human heart.bioRxiv : the preprint server for biology · 2026Article
- Microbiome and resistome dynamics in different stages of commercial broiler production with restricted antimicrobial use.BMC microbiology · 2026Article
122 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Motivation: Although seldom acknowledged explicitly, count data generated by sequencing platforms exist as compositions for which the abundance of each component (e.g. gene or transcript) is only coherently interpretable relative to other components within that sample. This property arises from the assay technology itself, whereby the number of counts recorded for each sample is constrained by an arbitrary total sum (i.e. library size). Consequently, sequencing data, as compositional data, exist in a non-Euclidean space that, without normalization or transformation, renders invalid many conventional analyses, including distance measures, correlation coefficients and multivariate statistical models. Results: The purpose of this review is to summarize the principles of compositional data analysis (CoDA), provide evidence for why sequencing data are compositional, discuss compositionally valid methods available for analyzing sequencing data, and highlight future directions with regard to this field of study. Supplementary information: Supplementary data are available at Bioinformatics online.
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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.