ArticleDatabase : the journal of biological databases and curation2020
Novel methods included in SpolLineages tool for fast and precise prediction of Mycobacterium tuberculosis complex spoligotype families.
Article in Database : the journal of biological databases and curation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed.
- Whole-genome sequencing analysis to identify antimicrobial resistance regions and virulence factors in Mycobacterium tuberculosis isolates from the Amhara Region, Ethiopia.Scientific reports · 2025Article
- Molecular typing of Mycobacterium tuberculosis: a review of current methods, databases, softwares, and analytical tools.FEMS microbiology reviews · 2025Review
- Genetic diversity ofNew microbes and new infections · 2024Article
- Population structure and spatial distribution of Mycobacterium tuberculosis in Ethiopia.Scientific reports · 2024Article
- Whole-genome sequencing-based genetic diversity, transmission dynamics, and drug-resistant mutations inFrontiers in public health · 2024Article
- Genetic diversity ofHeliyon · 2023Article
- Development, Evaluation, and Implementation of a House-Made Targeted Next-Generation Sequencing Spoligotyping in a French Laboratory.International journal of molecular sciences · 2022Article
- Consistency of Mycobacterium tuberculosis Complex Spoligotyping between the Membrane-Based Method andMicrobiology spectrum · 2022Article
- SITVITBovis-a publicly available database and mapping tool to get an improved overview of animal and human cases caused by Mycobacterium bovis.Database : the journal of biological databases and curation · 2022Article
- KaruBioNet: a network and discussion group for a better collaboration and structuring of bioinformatics in Guadeloupe (French West Indies).Bioinformatics advances · 2022Article
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4 authors.
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Abstract
Bioinformatic tools are currently being developed to better understand the Mycobacterium tuberculosis complex (MTBC). Several approaches already exist for the identification of MTBC lineages using classical genotyping methods such as mycobacterial interspersed repetitive units-variable number of tandem DNA repeats and spoligotyping-based families. In the recently released SITVIT2 proprietary database of the Institut Pasteur de la Guadeloupe, a large number of spoligotype families were assigned by either manual curation/expertise or using an in-house algorithm. In this study, we present two complementary data-driven approaches allowing fast and precise family prediction from spoligotyping patterns. The first one is based on data transformation and the use of decision tree classifiers. In contrast, the second one searches for a set of simple rules using binary masks through a specifically designed evolutionary algorithm. The comparison with the three main approaches in the field highlighted the good performances of our contributions and the significant runtime gain. Finally, we propose the 'SpolLineages' software tool (https://github.com/dcouvin/SpolLineages), which implements these approaches for MTBC spoligotype families' identification.
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