The documentation being quite heavy, it is not included in basic distributions. Please visit www.aevol.fr
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KNIBBE Carole
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This "new" mutagenesis tool is actually a resurrected version of a program David wrote for his PhD and which originally simulated similarity-based rearrangements only. I have ported it to version 4 and, more importantly, I have generalized it to all types of mutations, local or rearrangements, with random or similarity-based breakpoints. Lateral gene transfer, however, is not available yet for this tool. More precisely, this tool can be used to analyze a population evolved with lateral gene transfer, but only local mutations or intrachromosomal rearrangements can be performed in the mutagenesis analysis (for now). The mutagenesis can be performed for populations evolved on a spatial grid, with or without secretion. If secretion was enabled during the evolutionary run, the mutagenesis tool will report not only the metabolic error of the mutants, but also their secretion error. By contrast, the tool is not ready yet for plasmids, because right now trabnslocations between different genetic units is not managed yet. I will work on that in the following days. I added a man page for this tool, as well as a dedicated section in the user guide. I report below the main information necessary to use the tool. Usage: aevol_misc_mutagenesis -g GENER [-i INDEX | -r RANK] [-m MUTATIONTYPE] [-n NBMUTANTS] This tool creates and evaluates single mutants of an individual saved in a backup, by default the best of its generation. Use option -g to specify the generation number contanining the individual of interest. There must have been a backup of the population at this generation. Use either the -r RANK or the -i INDEX option to select another individual than the best one. The type of mutations to perform must be specified with the -m option. Choose 0 to create mutants with a point mutation, 1 for a small insertion, 2 for a small deletion, 3 for a duplication, 4 for a large deletion, 5 for a translocation or 6 for an inversion. For the point mutations, all single mutants will be created and evaluated. For the other mutation types, an exhaustive mutagenesis would take too much time, hence only a sample of mutants (1000 by default) will be generated. Use option -n to specify another sample size. The output file will be placed in a subdirectory called analysis-generationGENER.