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A rapid and simple method for assessing and representing genome sequence relatednessuse asterix (*) to get italics
M Briand, M Bouzid, G Hunault, M Legeay, M Fischer-Le Saux, M BarretPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"
<p>Coherent genomic groups are frequently used as a proxy for bacterial species delineation through computation of overall genome relatedness indices (OGRI). Average nucleotide identity (ANI) is a widely employed method for estimating relatedness between genomic sequences. However, pairwise comparisons of genome sequences based on ANI is relatively computationally intensive and therefore precludes analyses of large datasets composed of thousands of genome sequences. In this work we proposed a workflow to compute and visualize relationships between genomic sequences. A dataset containing more than 3,500 *Pseudomonas* genome sequences was successfully classified with an alternative OGRI based on *k*-mer counts in few hours with the same precision as ANI. A new visualization method based on zoomable circle packing was employed for assessing relationships among the 350 groups generated. Amendment of databases with these *Pseudomonas* groups greatly improved the classification of metagenomic read sets with *k*-mer-based classifier. The developed workflow was integrated in the user-friendly KI-S tool that is available at the following address:</p> should fill this box only if you chose 'All or part of the results presented in this preprint are based on data'. URL must start with http:// or https:// should fill this box only if you chose 'Scripts were used to obtain or analyze the results'. URL must start with http:// or https://
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ANI, k -mers, genome sequence relatedness, similarity matrix representation, circle packing, Pseudomonas , metagenome
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Bioinformatics, Metagenomics
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2019-11-07 16:37:56
B. Jesse Shapiro
Gavin Douglas