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Lessons Learned from Simulated Metagenomic Datasets

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Encyclopedia of Metagenomics

Definition

A simulation is the dynamic modeling of a real process over time. A simulated metagenomic dataset is the product of a single simulation iteration of the sequencing process of a microbial community under a specific set of sequencing-platform model parameters.

Summary

The use of simulations to produce model metagenomic datasets allows to test the performance of technological methodologies and the testing of theoretical hypothesis that cannot be achieved by empirical experimentation. Methodologically, it has been used to evaluate the performance of assembly programs and the effect of differences of read length and error rate on the quality of the resulting datasets. Theoretically, it has revealed biases and heterogeneity in the estimation of several diversity metrics from metagenomic samples. However, the full potential of the implementation of simulated datasets to metagenomics is still to be revealed.

Introduction

The complexity of microbial communities, and the nature of the...

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Correspondence to Germán Bonilla-Rosso .

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Bonilla-Rosso, G. (2013). Lessons Learned from Simulated Metagenomic Datasets. In: Nelson, K. (eds) Encyclopedia of Metagenomics. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6418-1_716-4

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  • DOI: https://doi.org/10.1007/978-1-4614-6418-1_716-4

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  • Online ISBN: 978-1-4614-6418-1

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