ArticleBioinformatics (Oxford, England)2021
mixtureS: a novel tool for bacterial strain genome reconstruction from reads.
Article in Bioinformatics (Oxford, England), 2021. 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.
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Who cites it
8 citing papers in PubMed.
- ZILA-SRM: a probabilistic framework with zero-inflated latent models for robust strain reconstruction from metagenomes.Microbiology spectrum · 2026Article
- MetaStrainer: accurate reconstruction of bacterial strain genotypes from short-read metagenomic samples.Bioinformatics (Oxford, England) · 2026Article
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- Scalable Microbial Strain Inference in Metagenomic Data Using StrainFacts.Frontiers in bioinformatics · 2022Article
- STRONG: metagenomics strain resolution on assembly graphs.Genome biology · 2021Article
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Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
motivationIt is essential to study bacterial strains in environmental samples. Existing methods and tools often depend on known strains or known variations, cannot work on individual samples, not reliable, or not easy to use, etc. It is thus important to develop more user-friendly tools that can identify bacterial strains more accurately.
resultsWe developed a new tool called mixtureS that can de novo identify bacterial strains from shotgun reads of a clonal or metagenomic sample, without prior knowledge about the strains and their variations. Tested on 243 simulated datasets and 195 experimental datasets, mixtureS reliably identified the strains, their numbers and their abundance. Compared with three tools, mixtureS showed better performance in almost all simulated datasets and the vast majority of experimental datasets. AVAILABILITY AND IMPLEMENTATION: The source code and tool mixtureS is available at http://www.cs.ucf.edu/˜xiaoman/mixtureS/. 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.