Evidence map›Paper›PMID 35138128›Full record

ArticlemSphere2022

The COMBAT-TB Workbench: Making Powerful Mycobacterium tuberculosis Bioinformatics Accessible.

Peter van Heusden, Ziphozakhe Mashologu, Thoba Lose, Robin Warren, Alan Christoffels

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in mSphere, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 34% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Article
  3. Discovering a novel glycosyltransferase geneFrontiers in microbiology · 2024
    Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 3 countries.

Peter van HeusdenSouth African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa.ORCID 0000-0001-6553-5274
Ziphozakhe MashologuSouth African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa.
Thoba LoseSouth African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa.
Robin WarrenDSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch Universitygrid.11956.3a, Cape Town, South Africa.
Alan ChristoffelsSouth African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa.ORCID 0000-0002-0420-2916
South African Medical Research Council · ZA

Funding

Medical Research Council
6 · The paper itself

Abstract

Whole-genome sequencing (WGS) is a powerful method for detecting drug resistance, genetic diversity, and transmission dynamics of Mycobacterium tuberculosis. Implementation of WGS in public health microbiology laboratories is impeded by a lack of user-friendly, automated, and semiautomated pipelines. We present the COMBAT-TB Workbench, a modular, easy-to-install application that provides a web-based environment for Mycobacterium tuberculosis bioinformatics. The COMBAT-TB Workbench is built using two main software components: the IRIDA platform for its web-based user interface and data management capabilities and the Galaxy bioinformatics workflow platform for workflow execution. These components are combined into a single easy-to-install application using Docker container technology. We implemented two workflows, for M. tuberculosis sample analysis and phylogeny, in Galaxy. Building our workflows involved updating some Galaxy tools (Trimmomatic, snippy, and snp-sites) and writing new Galaxy tools (snp-dists, TB-Profiler, tb_variant_filter, and TB Variant Report). The irida-wf-ga2xml tool was updated to be able to work with recent versions of Galaxy and was further developed into IRIDA plugins for both workflows. In the case of the M. tuberculosis sample analysis, an interface was added to update the metadata stored for each sequence sample with results gleaned from the Galaxy workflow output. Data can be loaded into the COMBAT-TB Workbench via the web interface or via the command line IRIDA uploader tool. The COMBAT-TB Workbench application deploys IRIDA, the COMBAT-TB IRIDA plugins, the MariaDB database, and Galaxy using Docker containers (https://github.com/COMBAT-TB/irida-galaxy-deploy).

Indexed as

Mycobacterium tuberculosisTuberculosisComputational BiologyHumansSoftwareWorkflowbioinformaticsmultidrug resistanceMycobacterium tuberculosis

Identifiers

PMID35138128
PMCPMC8827006
OpenAlexW4210922442

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.