Cloud-SPAN: Specialised analyses for environmental 'omics with Cloud-based High Performance Computing

This proposal aims to develop and deliver highly accessible resources that will upskill these interdisciplinary researchers so that they are able to generate and analyze big data relating to Environmental Biology using Cloud HPC. Although infrastructure and resources exist for microbial 'omics (e.g. JGI's IMG/M, MG-RAST, Galaxy, CLIMB, EBI) there is a lack of systematic training tightly linked to the EB domain and documentation is often focussed on technical proficiency rather than contextualised with a strong understanding of experimental design. We will provide foundational training and develop and deliver new advanced modules covering the specialised skills required to generate and analyse 'omics data using Cloud HPC resources. These will include experimental design and statistical modules to ensure researchers can generate data appropriate to investigate their research question. Modules will deploy cloud-based containerised instances provided by Google Education and Amazon Web Services (AWS) for exemplar workflows free to the learner. They will form a complete training resource with fully articulated prerequisites and learning objectives that can be used for in-person or online tutor-led workshops or self-paced learning. Our proposal offers structured Learning Paths from the statistical skills required for robust experimental design through to the reproducible execution and interpretation of 'omics analyses with HPC to cater to researchers with differing levels of previous experience and which allow self-assessment of training needs. We also provide Diversity Scholarships to enable members of underrepresented groups to participate in online or in-person training.