Spatial transcriptomics (ST) was named ‘Method of the Year 2020’ by Nature Methods and was more recently featured in Nature’s Seven technologies to watch in 2024. ST is now a prerequisite for researching transcriptional pathology at the cellular and molecular levels. Current use of ST is ubiquitously applied to multiple pathologies, including neurodegenerative disease, cancer, cardiomyopathy and nephrology. There is also an emerging application of ST in plant and microbiome research. While there are a plethora of spatial analysis applications, these are not unified or easily manageable by research scientists and they lack any hope of delivering FAIR and reproducible results.
To address this challenge, we will implement Spatial2Galaxy (S2G) – a self-contained, reproducible, scalable FAIR spatial transcription analysis platform for researchers and bioinformaticians alike. We will develop S2G based on our success with developing Galaxy workflows, training materials and ST and single-cell analysis pipelines.
S2G will provide state-of-the-art ST tools and workflows with proven high performance in benchmarking studies, ensuring the uptake of best practices. These tools will be demonstrated on datasets that connect various ST databases. This will consolidate community guidelines for integrative multi-modal single-cell omics and imaging analysis. Compared to non-spatial single-cell sequencing, presented as the Nature ‘Method of the Year 2013', it took six years until practical training and workflows for its analysis were FAIRified and available in Galaxy by 2019. In contrast, S2G aims to reduce this gap between technologies becoming relevant and provision of FAIR resources to the life science community for ST.
