Publication
Title
The MAGMA pipeline for comprehensive genomic analyses of clinical Mycobacterium tuberculosis samples
Author
Abstract
Background Whole genome sequencing (WGS) holds great potential for the management and control of tuberculosis. Accurate analysis of samples with low mycobacterial burden, which are characterized by low (<20x) coverage and high (>40%) levels of contamination, is challenging. We created the MAGMA (Maximum Accessible Genome for Mtb Analysis) bioinformatics pipeline for analysis of clinical Mtb samples.Methods and results High accuracy variant calling is achieved by using a long seedlength during read mapping to filter out contaminants, variant quality score recalibration with machine learning to identify genuine genomic variants, and joint variant calling for low Mtb coverage genomes. MAGMA automatically generates a standardized and comprehensive output of drug resistance information and resistance classification based on the WHO catalogue of Mtb mutations. MAGMA automatically generates phylogenetic trees with drug resistance annotations and trees that visualize the presence of clusters. Drug resistance and phylogeny outputs from sequencing data of 79 primary liquid cultures were compared between the MAGMA and MTBseq pipelines. The MTBseq pipeline reported only a proportion of the variants in candidate drug resistance genes that were reported by MAGMA. Notable differences were in structural variants, variants in highly conserved rrs and rrl genes, and variants in candidate resistance genes for bedaquiline, clofazmine, and delamanid. Phylogeny results were similar between pipelines but only MAGMA visualized clusters.Conclusion The MAGMA pipeline could facilitate the integration of WGS into clinical care as it generates clinically relevant data on drug resistance and phylogeny in an automated, standardized, and reproducible manner.
Language
English
Source (journal)
PLoS computational biology. - San Francisco, Calif.
Publication
San Francisco, Calif. : 2023
ISSN
1553-734X
1553-7358
DOI
10.1371/JOURNAL.PCBI.1011648
Volume/pages
19 :11 (2023) , p. 1-24
Article Reference
e1011648
ISI
001124342500002
Pubmed ID
38019772
Full text (Publisher's DOI)
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Project info
A personalized recommendation system for whole genome sequencing based and individualized tuberculosis treatment.
Development of a Centre for Whole Genome Sequencing studies of Mycobacterium.
Whole Genome Sequencing to streamline TB diagnosis, improve TB surveillance and optimize individualized TB treatment: a pragmatic trial.
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identifier
Creation 09.01.2024
Last edited 11.01.2024
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