A multi-omics graph database for data integration and knowledge extraction

Major recent advances in sequencing technologies have created new opportunities for studying the complex microbiome domain. However, microbial communities have many unknown roles and unclear impacts on their host environment. The increased availability of microbial omics data associated with heterogeneous metadata has the potential to revolutionize microbiome research. This study proposes a novel data-integration model and a practical pipeline to explore microbial community functions with the integration of omics data. Three case studies were employed to highlight the advanced abilities and applications of our graph database model. Furthermore, we show that a variety of information can be queried against our model and easily extracted using the proposed analysis pipeline. Our findings suggest that the proposed model is highly queryable and provides a critical analytical platform to extract useful knowledge from multi-omics data. We show that such knowledge extraction can lead to new discoveries, particularly when utilizing all available datasets.