rRbiMs, r tools for Reconstructing bin Metabolisms.
Mirna Vazquez Rosas Landa,Valerie de Anda Torres,Sahil Shan,Brett Baker The University of Texas at Austin
Abstract
Although microorganisms play a crucial role in the biogeochemical cycles and ecosystems, most of their diversity is still unknown. Understanding the metabolic potential of novel microbial genomes is an essential step to access this diversity. Most annotation pipelines use predefined databases to add the functional annotation. However, they do not allow the user to add metadata information, making it challenging to explore the metabolism based on a specific scientific question. Our motivation to build the package rRbiMs is to create a workflow that helps researchers to explore metabolism data in a reproducible manner. rRbiMs reads different database outputs and includes a new custom-curated database that the user can easily access. Its module-based design allows the user to choose between running the whole pipeline or just part of it. Finally, a key feature is that it facilitates the incorporation of metadata such as taxonomy and sampling data, allowing the user to answer specific questions of biological relevance. rRbiMs is a user-friendly R workflow that allows performing reproducible and accurate microbial metabolism analyses. We are working on the package looking forward to submitting it to R/Bioconductor and make it available for the research community.
Keywords: Metagenomics,Bin,MAG,Annotation,KEGG