Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

QuantTB - a method to classify mixed Mycobacterium tuberculosis infections within whole genome sequencing data.

BMC genomics - 28 Jan 2020

Anyansi Christine, Keo Arlin, Walker Bruce J, Straub Timothy J, Manson Abigail L, Earl Ashlee M, Abeel Thomas

Abstract excerpt

BACKGROUND: Mixed infections of Mycobacterium tuberculosis and antibiotic heteroresistance continue to complicate tuberculosis (TB) diagnosis and treatment. Detection of mixed infections has been limited to molecular genotyping techniques, which lack the sensitivity and resolution to accurately estimate the multiplicity of TB infections. In contrast, whole genome sequencing offers sensitive views of the genetic...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Algorithms
Share to Antitubercular Agents

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Databases, Genetic

Share to Drug Resistance, Bacterial

Share to Genome, Bacterial

Share to Mycobacterium tuberculosis

Share to Tuberculosis

Share to Whole Genome Sequencing

Source

Open in PubMed Open full text

Identifiers

PMID: 31992201
DOI: 10.1186/s12864-020-6486-3
PMCID: PMC6986090

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 3 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

QuantTB - a method to classify mixed Mycobacterium tuberculosis infections within whole genome sequencing data.PMID 31992201Read ↗

QuantTB – A method to classify mixed <i>Mycobacterium tuberculosis</i> infections within whole genome sequencing dataSemantic proximity Read ↗

TBtypeR: Sensitive detection and sublineage classification of low-frequency<i>Mycobacterium tuberculosis</i>complex mixed infectionsSemantic proximity Read ↗

Mixed-strain infection and heteroresistance in drug-resistant tuberculosis: insights from a whole-genome sequencing pilotSemantic proximity Read ↗

Identifying mixed Mycobacterium tuberculosis infections from whole genome sequence data.Semantic proximity Read ↗

A new method for detecting mixed Mycobacterium tuberculosis infection and reconstructing constituent strains provides insights into transmissionSemantic proximity Read ↗

Whole-Genome Sequencing Exhibits Better Diagnostic Performance than Variable-Number Tandem Repeats for Identifying Mixed Infections of Mycobacterium tuberculosis.Semantic proximity Read ↗

Mixed infections in genotypic drug-resistant Mycobacterium tuberculosis.Semantic proximity Read ↗

Mixed infections and heteroresistance of Mycobacterium tuberculosis among multidrug-resistant tuberculosis in China: a genomic epidemiology studySemantic proximity Read ↗

SAM-TB: a whole genome sequencing data analysis website for detection of <i>Mycobacterium tuberculosis</i> drug resistance and transmissionSemantic proximity Read ↗

A new method for detecting mixed <i>Mycobacterium tuberculosis</i> infection and reconstructing constituent strains provides insights into transmissionSemantic proximity Read ↗

A data compendium associating the genomes of 12,289 Mycobacterium tuberculosis isolates with quantitative resistance phenotypes to 13 antibiotics.Semantic proximity Read ↗

PhyResSE: a Web Tool Delineating Mycobacterium tuberculosis Antibiotic Resistance and Lineage from Whole-Genome Sequencing DataSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.