Bioinformatics Core

The Bioinformatics Core at UVA serves as a centralized resource for providing expert and timely bioinformatics consulting and data analysis solutions. The core offers services to investigators within and outside UVA on grant-funded and chargeback-based projects for the management and analysis of large-scale biological datasets produced by high-throughput genomics experiments. The Bioinformatics Core is located on the first floor in Pinn Hall (Room # 1312). 

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Core Goals

The core has three goals: provide analytical support for research using high-throughput biological data; provide outreach and bioinformatics training to the UVA community; and develop a unified
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Funding Models

The core has three funding models: fee-for-service consulting arrangements; departmental ‘retainer’ model; and core resource affiliate.
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Authorship

Get answers to frequently asked questions about authorship.
Current guidelines

Upcoming Workshop

RNA-Seq Analysis Part 1

This in-person, hands-on workshop is appropriate for students, staff, fellows and faculty working with high throughput transcriptomic data. This is the first part of a two-workshop series. Attendance at this session, or instructor permission, is required before taking RNA-Seq Analysis Part2. In this session you will learn the basics of high throughput RNA sequencing, including how to check the quality of your RNA-Seq reads, how to determine if reads contain adaptor sequences, and if so, how to identify and remove the adaptor sequence from raw RNA-Seq data. We will discuss all the basic points in detail. At the end of the workshop, you will learn how to connect to Rivanna and run an RNA-Seq pipeline (mapping and gene quantitation) on Rivanna or on your own system.

RNA-Seq Analysis Part 2

This in-person, hands-on workshop is appropriate for students, staff, fellows and faculty working with transcriptomics data. This is the second part of a two-workshop series. Attendance at RNA-Seq Analysis Part1, or instructor permission, is required before taking this session. In this session you will learn how to quantitate gene expression (making count table), learn the logic behind the read COUNTS, FPKM, TPM, and understand how to do differential gene expression analysis. The primary focus will be on the hands-on analysis of differential gene expression with RNA-Seq data using RStudio, and specialized packages like DESeq. You will also learn how to make a PCA plot, MA plot, Volcano plot and heatmap.

Services Provided

The UVA Bioinformatics Core provides statistical support and bioinformatics data analysis that will help explain the enormous amount of data typically generated from high-throughput microarray and next-generation sequencing experiments. The majority of the core’s services utilize a combination of open-source and custom-built software running under flexible and scalable workflow management systems. 

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