Predicting coarse-grained representations of biogeochemical cycles from metabarcoding data.

ABSTRACT:

Motivation

Taxonomic analysis of environmental microbial communities is now routinely performed thanks to advances in DNA sequencing. Determining the role of these communities in global biogeochemical cycles requires the identification of their metabolic functions, such as hydrogen oxidation, sulfur reduction, and carbon fixation. These functions can be directly inferred from metagenomics data, but in many environmental applications metabarcoding is still the method of choice. The reconstruction of metabolic functions from metabarcoding data and their integration into coarse-grained representations of biogeochemical cycles remains a difficult bioinformatics problem today.

Results

We developed a pipeline, called Tabigecy, which exploits taxonomic affiliations to predict metab

SUBMITTER: Belcour A 

PROVIDER: S-EPMC12261419 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature