Benchmarking microbiome transformations favors experimental quantitative approaches to address compositionality and sampling depth biases.

ABSTRACT: While metagenomic sequencing has become the tool of preference to study host-associated microbial communities, downstream analyses and clinical interpretation of microbiome data remains challenging due to the sparsity and compositionality of sequence matrices. Here, we evaluate both computational and experimental approaches proposed to mitigate the impact of these outstanding issues. Generating fecal metagenomes drawn from simulated microbial communities, we benchmark the performance of thirteen commonly used analytical approaches in terms of diversity estimation, identification of taxon-taxon associations, and assessment of taxon-metadata correlations under the challenge of varying microbial ecosystem loads. We find quantitative approaches including experimental procedures to incorporate

SUBMITTER: Llorens-Rico V 

PROVIDER: S-EPMC8196019 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature