Peer Community JournalBioinformaticsPeer-reviewed journal article
MacSyFinder v2: Improved modelling and search engine to identify molecular systems in genomes
Bertrand NéroniD, Rémi DeniseiD, Charles ColuzziiD, Marie TouchoniD, Eduardo P. C. RochaiD, Sophie S. AbbyiD
Abstract
Complex cellular functions are usually encoded by a set of genes in one or a few organized genetic loci in microbial genomes. Macromolecular System Finder (MacSyFinder) is a program that uses these properties to model and then annotate cellular functions in microbial genomes. This is done by integrating the identification of each individual gene at the level of the molecular system. We hereby present a major release of MacSyFinder (version 2) coded in Python 3. The code was improved and rationalized to facilitate future maintainability. Several new features were added to allow more flexible modelling of the systems. We introduce a more intuitive and comprehensive search engine to identify all the best candidate systems and sub-optimal ones that respect the models constraints. We also introduce the novel macsydata companion tool that enables the easy installation and broad distribution of the models developed for MacSyFinder (macsy-models) from GitHub repositories. Finally, we have updated and improved MacSyFinder popular models: TXSScan to identify protein secretion systems, TFFscan to identify type IV filaments, CONJscan to identify conjugative systems, and CasFinder to identify CRISPR associated proteins. MacSyFinder and the updated models are available at: https://github.com/gem-pasteur/macsyfinder and https://github.com/macsy-models.
- organism: bacteria (other)
- assay: whole-genome sequencing
- research focus: software / tool
- approach: statistical model
- Citations
- 177
- FWCI
- 15.77
- Field percentile
- top 1%
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