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In his recent publication Recovering Escherichia coli Plasmids in the Absence of Long-Read Sequencing Data Julian Paganini reviewed software tools to predict bacterial plasmids from sequencing data.
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Mobile genetic elements can be nested, like russian dolls. This is also the case for the vanA gene cluster in Enterococcus faecium, which is located on a Tn1546 transposon, which, in turn, is often located on plasmids.
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Update August 2021: The A.baumannii model is now integrated in mlplasmids
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Update 2020-04-11: Now published in Bioinformatics
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mlplasmids is an R package to predict if assembled short-read contigs from E. coli, K. pneunomiae or E. faecium originated from a plasmid or a chromosome. It uses species-specific machine learning classifiers which results in high precision and accuracy. mlplasmids can be used to predict the location of, for example, antibiotic resistance genes and the plasmidome content of a population of a bacterial species. The full description of mlplasmids is available as a preprint at bioRxiv.
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Here’s the poster presented by Sergio Arredondo Alonso at the 5th International Conference on Enterococci in Chamonix, FR.
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Recently we got back a round of reviews on a small review paper. There was one sentence in the text were I listed some SNP pipelines that I thought were good examples. The topic of the review is not pipelines so the intention was not to list all, just one or two. However reviewer 2 did not agree with my choice of examples. He suggested to omit the name of the pipeline that was unpublished and name a few other published ones instead.
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Here’s the poster presented at ‘Applied Bioinformatics and Public Health Microbiology 2017’ at the Wellcome Genome Campus, Hinxton, Cambridge, UK on the Enterococcus faecium plasmidome
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ggtree is a R package designed for viewing and annotating phylogenetic trees. It is based on the ggplot2 package. Here I will show step-by-step how to draw a tree with colored tips, because, even thought the bioconductor documentation is clear and complete, I did not read about this very common visualization.