ArticleBMC genomics2017
MetaTopics: an integration tool to analyze microbial community profile by topic model.
Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- LGTM: Gaussian process modulated neural topic modeling for longitudinal microbiome.Gut microbes · 2026Article
- Article
- An interpretable single-cell RNA sequencing data clustering method based on latent Dirichlet allocation.Briefings in bioinformatics · 2023Article
- Oral microbiome and ischemic stroke risk among elderly Chinese women.Journal of oral microbiology · 2023Article
- Fecal Bile Acids and Neutral Sterols Are Associated with Latent Microbial Subgroups in the Human Gut.Metabolites · 2022Article
- Associations between habitual diet, metabolic disease, and the gut microbiota using latent Dirichlet allocation.Microbiome · 2021Article
- Revealing the microbial assemblage structure in the human gut microbiome using latent Dirichlet allocation.Microbiome · 2020Article
- Model-based understanding of single-cell CRISPR screening.Nature communications · 2019Article
- CoreProbe: A Novel Algorithm for Estimating Relative Abundance Based on Metagenomic Reads.Genes · 2018Article
- Latent environment allocation of microbial community data.PLoS computational biology · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDeciphering taxonomical structures based on high dimensional sequencing data is still challenging in metagenomics study. Moreover, the common workflow processed in this field fails to identify microbial communities and their effect on a specific disease status. Even the relationships and interactions between different bacteria in a microbial community keep unknown.
resultsMetaTopics can efficiently extract the latent microbial communities which reflect the intrinsic relations or interactions among several major microbes. Furthermore, a quantitative measurement, Quetelet Index, is defined to estimate the influence of a latent sub-community on a certain disease status for given samples. An analysis of our in-house oral metagenomics data and public gut microbe data was presented to demonstrate the application and usefulness of MetaTopics. To preset a user-friendly R package, we have built a dedicated website, https://github.com/bm2-lab/MetaTopics , which includes free downloads, detailed tutorials and illustration examples.
conclusionsMetaTopics is the first interactive R package to integrate the state-of-arts topic model derived from statistical learning community to analyze and visualize the metagenomics taxonomy data.
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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.