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- W2094250612 abstract "Technological advances in next-generation sequencing-based approaches have greatly impacted the analysis of microbial community composition. In particular, 16S rRNA-based methods have been widely used to analyze the whole set of bacteria present in a target environment. As a consequence, several specific bioinformatic pipelines have been developed to manage these data. MetaGenome Rapid Annotation using Subsystem Technology (MG-RAST) and Quantitative Insights Into Microbial Ecology (QIIME) are two freely available tools for metagenomic analyses that have been used in a wide range of studies. Here, we report the comparative analysis of the same dataset with both QIIME and MG-RAST in order to evaluate their accuracy in taxonomic assignment and in diversity analysis. We found that taxonomic assignment was more accurate with QIIME which, at family level, assigned a significantly higher number of reads. Thus, QIIME generated a more accurate BIOM file, which in turn improved the diversity analysis output. Finally, although informatics skills are needed to install QIIME, it offers a wide range of metrics that are useful for downstream applications and, not less important, it is not dependent on server times." @default.
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- W2094250612 date "2014-01-01" @default.
- W2094250612 modified "2023-10-17" @default.
- W2094250612 title "Comparative Metagenomic Analysis of Human Gut Microbiome Composition Using Two Different Bioinformatic Pipelines" @default.
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- W2094250612 doi "https://doi.org/10.1155/2014/325340" @default.
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