Author Correction: Integrating standardized whole genome sequence analysis with a global Mycobacterium tuberculosis antibiotic resistance knowledgebase.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Whole genome sequencing of Mycobacterium tuberculosis: current standards and open issues.

Whole genome sequencing (WGS) of Mycobacterium tuberculosis has rapidly progressed from a research tool to a clinical application for the diagnosis and management of tuberculosis and in public health surveillance. This development has been facilitated by drastic drops in cost, advances in technology and concerted efforts to translate sequencing data into actionable information. There is, however, a risk that, in the absence of a consensus and international standards, the widespread use of WGS technology may result in data and processes that lack harmonization, comparability and validation.

Beyond multidrug resistance: Leveraging rare variants with machine and statistical learning models in Mycobacterium tuberculosis resistance prediction.

Background: The diagnosis of multidrug resistant and extensively drug resistant tuberculosis is a global health priority. Whole genome sequencing of clinical Mycobacterium tuberculosis isolates promises to circumvent the long wait times and limited scope of conventional phenotypic antimicrobial susceptibility, but gaps remain for predicting phenotype accurately from genotypic data especially for certain drugs. Our primary aim was to perform an exploration of statistical learning algorithms and genetic predictor sets using a rich dataset to build a high performing and fast predicting model to detect anti-tuberculosis drug resistance.

Enabling precision medicine via standard communication of HTS provenance, analysis, and results.

A personalized approach based on a patient's or pathogen's unique genomic sequence is the foundation of precision medicine. Genomic findings must be robust and reproducible, and experimental data capture should adhere to findable, accessible, interoperable, and reusable (FAIR) guiding principles. Moreover, effective precision medicine requires standardized reporting that extends beyond wet-lab procedures to computational methods.

Integrating standardized whole genome sequence analysis with a global Mycobacterium tuberculosis antibiotic resistance knowledgebase.

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.

Fine-scale differentiation between and group signatures in metagenome shotgun data.

Background: It is possible to detect bacterial species in shotgun metagenome datasets through the presence of only a few sequence reads. However, false positive results can arise, as was the case in the initial findings of a recent New York City subway metagenome project. False positives are especially likely when two closely related are present in the same sample.

Validation of Novel Mycobacterium tuberculosis Isoniazid Resistance Mutations Not Detectable by Common Molecular Tests.

Resistance to the first-line antituberculosis (TB) drug isoniazid (INH) is widespread, and the mechanism of resistance is unknown in approximately 15% of INH-resistant (INH-R) strains. To improve molecular detection of INH-R TB, we used whole-genome sequencing (WGS) to analyze 52 phenotypically INH-R complex (MTBC) clinical isolates that lacked the common S315T or promoter mutations. Approximately 94% (49/52) of strains had mutations at known INH-associated loci that were likely to confer INH resistance.

Mycobacterial biomaterials and resources for researchers.

There are many resources available to mycobacterial researchers, including culture collections around the world that distribute biomaterials to the general scientific community, genomic and clinical databases, and powerful bioinformatics tools. However, many of these resources may be unknown to the research community. This review article aims to summarize and publicize many of these resources, thus strengthening the quality and reproducibility of mycobacterial research by providing the scientific community access to authenticated and quality-controlled biomaterials and a wealth of information, analytical tools and research opportunities.

A standardised method for interpreting the association between mutations and phenotypic drug resistance in .

A clear understanding of the genetic basis of antibiotic resistance in is required to accelerate the development of rapid drug susceptibility testing methods based on genetic sequence.Raw genotype-phenotype correlation data were extracted as part of a comprehensive systematic review to develop a standardised analytical approach for interpreting resistance associated mutations for rifampicin, isoniazid, ofloxacin/levofloxacin, moxifloxacin, amikacin, kanamycin, capreomycin, streptomycin, ethionamide/prothionamide and pyrazinamide. Mutation frequencies in resistant and susceptible isolates were calculated, together with novel statistical measures to classify mutations as high, moderate, minimal or indeterminate confidence for predicting resistance.

Population structure of Neisseria gonorrhoeae based on whole genome data and its relationship with antibiotic resistance.

Neisseria gonorrhoeae is the causative agent of gonorrhea, a sexually transmitted infection (STI) of major importance. As a result of antibiotic resistance, there are now limited options for treating patients. We collected draft genome sequence data and associated metadata data on 76 N.

Evaluating rare variants in complex disorders using next-generation sequencing.

Determining the genetic architecture of liability for complex neuropsychiatric disorders like autism spectrum disorders and schizophrenia poses a tremendous challenge for contemporary biomedical research. Here we discuss how genetic studies first tested, and rejected, the hypothesis that common variants with large effects account for the prevalence of these disorders. We then explore how the discovery of structural variation has contributed to our understanding of the etiology of these disorders.