in metagenomic data analysis comprises the assembly of the sequenced assembly tools have been published in the last years targeting data coming from on sequencing (NGS) technologies but these assemblers have not been designed n multi-genome scenarios that characterize metagenomic studies. Here we cal assessment of current de novo short reads assembly tools in multi-genome ng complex simulated metagenomic data. With this approach we tested the erent assemblers in metagenomic studies demonstrating that even under the positions the number of chimeric contigs involving different species is e further showed that the assembly process reduces the accuracy of the ssification of the metagenomic data and that these errors can be overcome verage of the studied metagenome. The results presented here highlight the iculties that de novo genome assemblers face in multi-genome scenarios g that these difficulties, that often compromise the functional classification of data, can be overcome with a high sequencing effort.
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