ArticleGenome biology2020
Approaches for integrating heterogeneous RNA-seq data reveal cross-talk between microbes and genes in asthmatic patients.
Article in Genome biology, 2020. 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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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
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Who cites it
8 citing papers in PubMed.
- Profiling Peripheral Blood with an Optimized, Multiplexed, Single-cell Multiome Approach Supports an Insulin-driven Asthma Subtype.bioRxiv : the preprint server for biology · 2026Article
- Preventive and Ameliorative Effects of Alanine Supplementation on High-Fat Diet-Induced Obesity and Metabolic Dysfunction via the Gut-Liver-Adipose Axis in C57BL/6J Mice.Foods (Basel, Switzerland) · 2026Article
- The gut-lung axis in childhood asthma: from early-life programming to microbiome-informed precision medicine-a narrative review.Frontiers in immunology · 2026Review
- Global Research Trends in Childhood Asthma and the Microbiome: A Bibliometric Analysis of 2000 to 2024.Journal of multidisciplinary healthcare · 2025Article
- A topic modeling approach reveals the dynamic T cell composition of peripheral blood during cancer immunotherapy.Cell reports methods · 2023Article
- An interpretable single-cell RNA sequencing data clustering method based on latent Dirichlet allocation.Briefings in bioinformatics · 2023Article
- Uncovering the hidden structure of dynamic T cell composition in peripheral blood during cancer immunotherapy: a topic modeling approach.bioRxiv : the preprint server for biology · 2023Article
- Single-cell RNA-sequencing in asthma research.Frontiers in immunology · 2022Review
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
Sputum induction is a non-invasive method to evaluate the airway environment, particularly for asthma. RNA sequencing (RNA-seq) of sputum samples can be challenging to interpret due to the complex and heterogeneous mixtures of human cells and exogenous (microbial) material. In this study, we develop a pipeline that integrates dimensionality reduction and statistical modeling to grapple with the heterogeneity. LDA(Latent Dirichlet allocation)-link connects microbes to genes using reduced-dimensionality LDA topics. We validate our method with single-cell RNA-seq and microscopy and then apply it to the sputum of asthmatic patients to find known and novel relationships between microbes and genes.
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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.