Bioinformatics & Genomics

UVA Research Computing (RC) can help with your bioinformatics project.

Next-generation sequence data analysis

RC staff can help you start to use popular bioinformatics software for functions such as

  • Genome assembly, reference-based and/or de-novo
  • Whole-Genome/Exome sequence analysis for variant calling/annotation
  • RNA-Seq data analysis to quantify, discover and profile RNAs
  • Mircobiome data analysis, including 16S rRNA surveys, OTU clustering, microbial profiling, taxonomic and functional analysis from whole shotgun metagenomic/metatranscriptomic datasets
  • Epigenetic analysis from BSAS/ChIP-Seq/ATAC-Seq

Computing Platforms

UVA has three computing facilities available to researchers: Rivanna and Afton, for non-sensitive data, and Ivy, for sensitive data. In addition, cloud-based services offer a computing environment for running flexible, scalable on-demand applications. RC can work with your team to determine the computing platform best suited for your research project.

Rivanna and Afton

High-performance Computing Clusters

Rivanna and Afton are the university's high-performance computing systems for high-throughput multithreaded jobs, parallel jobs, and memory intensive large-scale data analyses. The architecture is specifically suited for large scale distributed genomic data analysis, with many 100+ bioinformatics software packages installed and ready to use.

Ivy

High-Security / HIPAA Computing

Ivy is a HIPAA and CUI compliant cluster at UVA for working with sensitive data. Researchers have access to a group of bioinformatics software on Ivy Linux VMs.

Cloud Computing

We can explore the possibility of using cloud infrastructure (AWS/GCP) for your bioinformatics analysis and data storage. For certain applications, the 'elasticity' of cloud computing may prove beneficial for saving time and reducing costs of data analysis and sharing. The RC team is available for consultation on your project needs.

Consulting

We can assist with choosing the right package, developing a workflow, porting it to one of our computing platforms, and running the jobs.

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