Workshop - Microbiome data interpretation

Studying microbiomes using metagenomic sequence data is a topic of major scientific importance, for example due to the impact of human microbiota in human health, or the impact of environmental microbiota in our daily life. Scientists are now generating an exponentially increasing amount of microbiome-derived sequence data, and this trend is expected to continue as sequencing costs are currently falling. The major bottleneck in microbiome studies is to interpret this complex data in the context of existing literature and datasets, which can sometimes take years. Thus there is an urgent need to accelerate the interpretation phase of microbiome data analysis. Text mining can help with this by systematically annotating the biomedical literature with organisms, processes, environments and associations among them. Interactive text-mining tools can furthermore be used to speed up standards-compliant annotation of environmental descriptors for existing datasets, which is important to facilitate comparisons. However, most microbiome analysts are unaware of the power of text mining. The proposed practical course will provide hands-on training to participants in handling metagenomic sequence data, generating taxonomic/functional summaries, performing statistical analysis based on a case-control scenario as example, and interpreting the results using automated text mining tools. Participants will gather new knowledge about microbiome analysis and text mining. They will learn how to use state-of-the-art analysis tools to efficiently interpret results. Participants will also learn how to use computerome, the largest supercomputer in Denmark, to analyse large microbiome datasets. The aim is that this will speed up data interpretation and knowledge generation to match the fast pace with which raw data are generated.