ArticleScientific reports2018
Integrating standardized whole genome sequence analysis with a global Mycobacterium tuberculosis antibiotic resistance knowledgebase.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 56 papers, 3 of them syntheses that pooled it.
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
56 citing papers in PubMed, 3 syntheses or guidelines pooled it, 101 citations in OpenAlex.
- Open-access genomic drug resistance prediction tools forJournal of clinical microbiology · 2026Pooled it
- Systematic review of mutations associated with resistance to the new and repurposed Mycobacterium tuberculosis drugs bedaquiline, clofazimine, linezolid, delamanid and pretomanid.The Journal of antimicrobial chemotherapy · 2020Pooled it
- Whole-Genome Sequencing as Tool for Investigating International Tuberculosis Outbreaks: A Systematic Review.Frontiers in public health · 2019Pooled it
- Targeted next-generation sequencing of sputum for diagnosis of drug-resistant TB: results of a national survey in Democratic Republic of the Congo.Scientific reports · 2020Trial
- Algorithmic Determinants of Performance Heterogeneity in Whole-Genome Sequencing-Based Prediction of Drug Resistance inMicroorganisms · 2026Review
- Machine learning-based analysis of drug resistance mutations in Mycobacterium tuberculosis.PloS one · 2026Article
- Comparative Analysis of Virulence Genes in Non-Tuberculosis Mycobacteria (NTM) Isolated from Kenyan Camel Milk Suggests Potential Pathogenicity.Current microbiology · 2025Article
- Reference-Free Variant Calling with Local Graph Construction with ska lo (SKA).Molecular biology and evolution · 2025Article
- Machine learning-based approach for identification of new resistance associated mutations from whole genome sequences ofBioinformatics advances · 2025Article
- Droplet based whole genome amplification for sequencing minute amounts of purified Mycobacterium tuberculosis DNA.Scientific reports · 2024Article
- GenoMycAnalyzer: a web-based tool for species and drug resistance prediction for Mycobacterium genomes.BMC genomics · 2024Article
- Estimation of country-specific tuberculosis resistance antibiograms using pathogen genomics and machine learning.BMJ global health · 2024Article
- The MAGMA pipeline for comprehensive genomic analyses of clinical Mycobacterium tuberculosis samples.PLoS computational biology · 2023Article
- Article
- Operationalising targeted next-generation sequencing for routine diagnosis of drug-resistant TB.Public health action · 2023Article
- Transmission Dynamics of a Mycobacterium tuberculosis Complex Outbreak in an Indigenous Population in the Colombian Amazon Region.Microbiology spectrum · 2023Article
- Updated considerations in the diagnosis and management of tuberculosis infection and disease: integrating the latest evidence-based strategies.Expert review of anti-infective therapy · 2023Review
- Analysis of Genome-Wide Mutational Dependence in Naturally Evolving Mycobacterium tuberculosis Populations.Molecular biology and evolution · 2023Article
- CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database.Nucleic acids research · 2023Article
- TransFlow: a Snakemake workflow for transmission analysis of Mycobacterium tuberculosis whole-genome sequencing data.Bioinformatics (Oxford, England) · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
29 authors at 19 institutions in 12 countries.
Funding
Abstract
Drug-resistant tuberculosis poses a persistent public health threat. The ReSeqTB platform is a collaborative, curated knowledgebase, designed to standardize and aggregate global Mycobacterium tuberculosis complex (MTBC) variant data from whole genome sequencing (WGS) with phenotypic drug susceptibility testing (DST) and clinical data. We developed a unified analysis variant pipeline (UVP) ( https://github.com/CPTR-ReSeqTB/UVP ) to identify variants and assign lineage from MTBC sequence data. Stringent thresholds and quality control measures were incorporated in this open source tool. The pipeline was validated using a well-characterized dataset of 90 diverse MTBC isolates with conventional DST and DNA Sanger sequencing data. The UVP exhibited 98.9% agreement with the variants identified using Sanger sequencing and was 100% concordant with conventional methods of assigning lineage. We analyzed 4636 publicly available MTBC isolates in the ReSeqTB platform representing all seven major MTBC lineages. The variants detected have an above 94% accuracy of predicting drug based on the accompanying DST results in the platform. The aggregation of variants over time in the platform will establish confidence-graded mutations statistically associated with phenotypic drug resistance. These tools serve as critical reference standards for future molecular diagnostic assay developers, researchers, public health agencies and clinicians working towards the control of drug-resistant tuberculosis.
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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.