MacSyFinder v2: An improved search engine to model and identify molecular systems in genomes
Résumé
Complex cellular functions are most often encoded by a set of genes rather than individual
ones. Furthermore, the genes in such “systems” are often encoded nearby in microbial genomes.
MacSyFinder uses these properties to model and then accurately annotate cellular functions in
microbial genomes at the system-level rather than at the individual-gene level. We hereby present a
major release of MacSyFinder [1], MacSyFinder version 2 (v2). This new version is coded in
Python 3 (>= 3.7). The code was improved and rationalized to enable higher maintainability over
time. Several new features were added to allow more flexible modeling of the systems. We
introduce a more intuitive and comprehensive search engine to identify all the best candidate
systems and sub-optimal ones that still respect the models’ constraints. We also present 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,
improved, and made available MacSyFinder popular models to this novel version: TXSScan and
TFF-SF, CONJscan, and CasFinder. MacSyFinder v2 can be found at this URL:
https://github.com/gem-pasteur/macsyfinder
References
1. Sophie S Abby, Bertrand Néron, Hervé Ménager, Marie Touchon, Eduardo PC Rocha. MacSyFinder: A Program to
Mine Genomes for Molecular Systems with an Application to CRISPR-Cas Systems. PLOS ONE,
https://doi.org/10.1371/journal.pone.0110726, 2014.
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