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DATA ANALYSIS & STORAGЕ - Revealing, comparing and storing biodiversity patterns in massive amplicon datasets
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Edited by Diego Fontaneto, Alain Franc, Alex Weigand, Agnès Bouchez, Florian Leese

Analyses of biodiversity data from metagenomics face two main issues: one on storing and maintaining a large amount of data in online repositories, and the other one on having comparable pipelines to process data. Data processing aims at revealing biodiversity patterns and bridging these patterns with tools and models in statistical ecology. The session will explore the details of the current and expected approaches (i) for storage of raw data and data processing outcomes of massive datasets compliant with FAIR principles, (ii) in the available pipelines to obtain Operational Taxonomic Units, Amplicon Sequence Variants, and other basic units of diversity from massive sequencing; showcasing examples, advantages, caveats, and pitfalls. The main aims are to foster our understanding of biodiversity patterns at different scales by producing reliable and reusable data and pipelines downstream of massive sequencing and thus, enabling cross comparisons.

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