ArticleFrontiers in genetics2021
tascCODA: Bayesian Tree-Aggregated Analysis of Compositional Amplicon and Single-Cell Data.
Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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.
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Who cites it
12 citing papers in PubMed, 15 citations in OpenAlex.
- Multi-omic single nuclei profiling of murine pancreas shows dynamic epigenetic heterogeneity of acinar cells.Cell death and differentiation · 2026Article
- A phylogeny-guided framework for decoding mechanisms of human endogenous retrovirus regulation in health and disease.bioRxiv : the preprint server for biology · 2026Article
- Score Matching for Differential Abundance Testing of Compositional High-Throughput Sequencing Data.Statistics in medicine · 2026Article
- Cellular and molecular landscapes of human tendons across the lifespan revealed by spatial and single-cell transcriptomics.Cell reports · 2026Article
- Pertpy: an end-to-end framework for perturbation analysis.Nature methods · 2026Article
- Single-cell differential abundance detection: A new angle on dissecting tumor heterogeneity.World journal of clinical oncology · 2026Review
- Tree-based differential testing using inferential uncertainty for RNA-seq.Genome research · 2025Article
- Tree-based differential testing using inferential uncertainty for RNA-Seq.bioRxiv : the preprint server for biology · 2025Article
- Variational inference for microbiome survey data with application to global ocean data.ISME communications · 2025Article
- Analysis of Microbiome Data.Annual review of statistics and its application · 2024Article
- Best practices for single-cell analysis across modalities.Nature reviews. Genetics · 2023Review
- Negative binomial factor regression with application to microbiome data analysis.Statistics in medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate generative statistical modeling of count data is of critical relevance for the analysis of biological datasets from high-throughput sequencing technologies. Important instances include the modeling of microbiome compositions from amplicon sequencing surveys and the analysis of cell type compositions derived from single-cell RNA sequencing. Microbial and cell type abundance data share remarkably similar statistical features, including their inherent compositionality and a natural hierarchical ordering of the individual components from taxonomic or cell lineage tree information, respectively. To this end, we introduce a Bayesian model for
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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.