Abstract
Viruses are the most abundant and diverse biological entity in the earth. Nowadays, there are several viral metagenomes from different ecological niches which have been used to characterize new viral particles and to determine their diversity. However, viral metagenomic data have the disadvantage to be high-dimensional compositional and sparse. This type of data renders many of the conventional multivariate statistical analyses inoperative. Fortunately, different libraries and statistical packages have been developed to deal with this problem and perform the different ecological and statistical analyses. In the present chapter, it is analyzed simulated viral metagenomes, based on real human gut-associated viral metagenomes, using different R and python packages. The example presented here includes the estimation and comparison of different indexes of diversity, evenness, and richness; perform different ordination and statistical analysis using different dissimilarity metrics; determine the optimal cluster configuration and perform biomarker discovery. The scripts and the simulated datasets are in https://github.com/jorgevazcast/Viromic-diversity
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Vázquez-Castellanos, J. (2018). Diversity Analysis in Viral Metagenomes. In: Moya, A., Pérez Brocal, V. (eds) The Human Virome. Methods in Molecular Biology, vol 1838. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8682-8_15
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DOI: https://doi.org/10.1007/978-1-4939-8682-8_15
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