• Container Service Request

    – Name * E-mail * User ID * Classification * - Select -FacultyStaffPostdoctoral AssociateOther Affiliation * - Select - College of Arts & Sciences School of Data Science School of Engineering and Applied Sciences School of Medicine Darden School of Business UVA Health System Other Project Summary Please describe your project and the container images you want to run. Tier of Service *     6 - 15 containers ($10/month total)   15 containers ($48/month total) Billing Tiers are selected and paid for by the PI.
  • Microservices

    Microservice architecture is an approach to designing and running applications. Such applications are typically run within containers, made popular in the last few years by Docker. Containers are portable, efficient, and disposable, and contain code and any dependencies in a single package. Containerized microservices typically run a single process, rather than an entire stack within the same computing environment. This allows portions of your application to be easily replaced or scaled as needed. Microservices at UVA Research Computing runs microservices in a clustered orchestration environment that automates the deployment and management of many containers easy and scalable. This cluster has >1000 cores and ~1TB of memory allocated to running containerized services.
  • Software Containers

    Overview Containers bundle an application, the libraries and other executables it may need, and even the data used with the application into portable, self-contained files called images. Containers simplify installation and management of software with complex dependencies and can also be used to package workflows. Singularity is a container application targeted to multi-user, high-performance computing systems. It interoperates well with SLURM and with the Lmod modules system. Singularity can be used to create and run its own containers, or it can import Docker containers. Creating Singularity Containers To create your own image from scratch, you must have root privileges on some computer running Linux (any version).
  • LOLAweb

    LOLAweb The past few years have seen an explosion of interest in understanding the role of regulatory DNA. This interest has driven large-scale production of functional genomics data resources and analytical methods. One popular analysis is to test for enrichment of overlaps between a query set of genomic regions and a database of region sets. In this way, annotations from external data sources can be easily connected to new genomic data. SOM Research Computing is working with faculty in the UVA Center for Public Health Genomics to implement LOLAweb, an online tool for performing genomic locus overlap annotations and analyses. This project, written in the statistical programming language R, allows users to specify region set data in BED format for automated enrichment analysis.
  • Refgenie: A Reference Genome Resource Manager

    Reference genome assemblies are essential for high-throughput sequencing analysis projects. Typically, genome assemblies are stored on disk alongside related resources; e.g., many sequence aligners require the assembly to be indexed. The resulting indexes are broadly applicable for downstream analysis, so it makes sense to share them. However, there is no simple tool to do this. Refgenie is a reference genome assembly asset manager. Refgenie makes it easier to organize, retrieve, and share genome analysis resources. In addition to genome indexes, refgenie can manage any files related to reference genomes, including sequences and annotation files. Refgenie includes a command line interface and a server application that provides a RESTful API, so it is useful for both tool development and analysis.