ArticleMicrobial genomics2016
Bayesian identification of bacterial strains from sequencing data.
Article in Microbial genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 24 citations in OpenAlex.
- Alterations of human skin microbiome and expansion of antimicrobial resistance after systemic antibiotics.Science translational medicine · 2021Trial
- Longitudinal profiling of low-abundance strains in microbiomes with ChronoStrain.Nature microbiology · 2025Article
- Staphylococcal diversity in atopic dermatitis from an individual to a global scale.Cell host & microbe · 2023Article
- Article
- MetaPop: a pipeline for macro- and microdiversity analyses and visualization of microbial and viral metagenome-derived populations.Microbiome · 2022Article
- StrainGE: a toolkit to track and characterize low-abundance strains in complex microbial communities.Genome biology · 2022Article
- Contaminant DNA in bacterial sequencing experiments is a major source of false genetic variability.BMC biology · 2020Article
- QuantTB - a method to classify mixed Mycobacterium tuberculosis infections within whole genome sequencing data.BMC genomics · 2020Article
- High-resolution sweep metagenomics using fast probabilistic inference.Wellcome open research · 2020Article
- Computational Methods for Strain-Level Microbial Detection in Colony and Metagenome Sequencing Data.Frontiers in microbiology · 2020Review
- MentaLiST - A fast MLST caller for large MLST schemes.Microbial genomics · 2018Article
- A bit of a mouthful.Nature reviews. Microbiology · 2016Article
- Bayesian identification of bacterial strains from sequencing data.Microbial genomics · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 5 institutions in 4 countries.
Funding
Abstract
Rapidly assaying the diversity of a bacterial species present in a sample obtained from a hospital patient or an environmental source has become possible after recent technological advances in DNA sequencing. For several applications it is important to accurately identify the presence and estimate relative abundances of the target organisms from short sequence reads obtained from a sample. This task is particularly challenging when the set of interest includes very closely related organisms, such as different strains of pathogenic bacteria, which can vary considerably in terms of virulence, resistance and spread. Using advanced Bayesian statistical modelling and computation techniques we introduce a novel pipeline for bacterial identification that is shown to outperform the currently leading pipeline for this purpose. Our approach enables fast and accurate sequence-based identification of bacterial strains while using only modest computational resources. Hence it provides a useful tool for a wide spectrum of applications, including rapid clinical diagnostics to distinguish among closely related strains causing nosocomial infections. The software implementation is available at https://github.com/PROBIC/BIB.
Indexed as
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What OpenQuestion holds
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.