There is significant consensus that the alteration of tissue microenvironment in pancreatic tissue (e.g., infiltration of immune cells, β-cell death, fibrosis) is involved in several pancreatic pathologies. My current project aims to set up a computational infrastructure to analyze spatial transcriptomics data of pancreatic tissue. I will optimize the computational methodology to study spatial transcriptomics data from pancreatic biopsies from healthy donors and donors with different types of pancreatic diseases. To do this, I will, among other things, generate spatial transcriptomics data and run FASTQ files through Snakemake/Nextflow pipelines via Singularity. I will also use different data analysis and exploration tools such as Cell2Deconvolution. In this project, I am in need of storage and computational resources to store and run my pipelines and data to perform proper evaluation. From the usage distribution of the previous year, I realized that I used more resources than I had planned for in my initial proposal: ‘My current first sample takes about 500 CPU hours, and I will analyze about 25 of these samples (totalling approximately 25x500 CPU hours). To also allow time for troubleshooting and interactive sessions, I require an additional 5x1000 core-hours. I have previously worked on my local computer and using cloud services, but I do not see this strategy as sustainable anymore. As I, in the previous round, used approximately a total of 165 X 1000 core-h. Hence, I will use this as a motivation behind asking for the maximum number of core-h hours available. Classification: Bioinformatics, Computational Biology, Transcriptomics, Medicine, Biomedical Science