See more events & classes

Check out the Summer Education Series from UVA Research Computing (RC). RC staff are teaching a series of free, hands-on workshops this summer that are open to all UVA researchers. Space is limited, so register now! Topics include Python, R, MATLAB, high performance computing, and more.

The Claude Moore Health Sciences Library is located at 1350 Jefferson Park Avenue between McKim Hall and Pinn Hall (formerly Jordan Hall).

Access to Health System buildings is limited to those with a Health System ID, however, several entrances have accommodations for visitors. Please see the map below for entrances convenient to main Grounds. Entrances indicated with a red arrow have a "doorbell" to request access. The main entrance to West Complex (indicated by a green arrow) is publicly accessible, as is the main entrance to the University Hospital.

If you have questions about accessing the Library, please contact the HSL Service Desk at 434-924-5444.

Intro to RNASeq - May 22

Install BiocManager if necessary

if (!requireNamespace("BiocManager", quietly = TRUE))
  install.packages("BiocManager")

Install the following packages using BiocManager, example BiocManager::install("DESeq2")

• DESeq2
• recount
• biomaRt
• gage -gageData
• pathview

BiocManager::install("recount")
library(recount)

BiocManager::install("DESeq2")
library(DESeq2)

BiocManager::install("biomaRt")
library(biomaRt)

BiocManager::install("gage")
library(gage)

BiocManager::install("pathview")
library(pathview)

BiocManager::install("gageData")
library(gageData)

Intro R: May 14

Winter/Spring 2019 

Data Analysis, Visualization, and Research Software Workshops

Introduction to R
Introduction to SPSS
Data Visualization in R with ggplot2
Data Preparation: Taming wild data with R
Essential Skills for Data in Excel
Essential Statistics with R
Power and Sample Size in R
Predictive Analytics with R
Managing R Libraries
Reproducible Research Using RMarkdown and GitHub
Interactive Visualization with R using Shiny
Regression in R
Introduction to RNASeq
Single cell RNASeq with Seurat
Introduction to QGIS
Qualitative Data Analysis and Introduction to Dedoose
​Introduction to SAS
Funding Discovery Workshop
Introduction to Qualtrics
Introduction to scientific image processing with Fiji/ImageJ
Automation of image processing with Fiji/ImageJ
Introduction to NCBI Resources

Fall 2018 

Data Analysis, Visualization, and Research Software Workshops

Introduction to R
Introduction to SPSS
Data Visualization in R with ggplot2
Data Preparation: Taming wild data with R
Essential Skills for Data in Excel
Essential Statistics with R
Introduction to QGIS
Introduction to Stata
​Introduction to SAS
Funding Discovery Workshop
Introduction to Qualtrics
Introduction to scientific image processing with Fiji/ImageJ
​SciFinder Skills Enhancement
Reaxys Medicinal Chemistry
Introduction to NCBI Resources
Regression in R
Automation of image processing with Fiji/ImageJ
Predictive Analytics with R
Building Shiny Web Applications in R

Winter/Spring 2018 

Data Analysis, Visualization, and Research Software Workshops

Introduction to R
Introduction to SPSS
Data Manipulation in R with dplyr
Managing Your Spreadsheet Data
Interactive Visualization with R
Predictive Analytics with R
Funding Discovery Workshop
Survey Design with Analysis in Mind (Qualtrics)
Data Manipulation in R with dplyr
Essential Statistics with R
Using SPSS Syntax
Introduction to SAS
Building Shiny Web Applications in R
Data Visualization in R with ggplot2
Predictive Analytics with R
Essential Statistics with R
Using SPSS Syntax
 

Fall 2017

Data Analysis, Visualization, and Computing Workshops

Coordinated under the UVA BioConnector branding, these workshops were led by SOM Research Computing, Health Sciences Library, Public Health Sciences, University Library, and Advanced Research Computing Services

Advanced Data Manipulation with R - 2017-10-03
Advanced Data Visualization with ggplot2 - 2017-10-30
Automated Image Analysis with ImageJ - 2017-10-19
Building Shiny Web Applications in R - 2017-04-18
Data cleansing in Python using Pandas and the Jupyter Notebook - 2017-10-09
Data visualization in Python - 2017-10-12
Essential Statistics with R - 2017-11-13
Introduction to Cloud Computing with AWS - 2017-09-26
Introduction to the Command Line - 2017-09-07
Introduction to Dedoose- 2017-10-31
Introduction to Docker Containers - 2017-10-31
Introduction to Git and GitHub 2017-09-22
Introduction to Ivy - 2017-09-19
Introduction to Matlab - 2017-11-07
Introduction to Python - 2017-09-05, 2017-09-11
Introduction to R - 2017-09-06, 2017-09-12
Introduction to Rivanna - 2017-09-21, 2017-11-01
Introduction to SAS - 2017-09-27
Introduction to Scientific Image Processing with Fiji/ImageJ, 2017-10-10
Introduction to SPSS - 2017-09-20
Organizing Your Spreadsheet Data - 2017-09-28, 2017-11-07
​Overview of UVA Research Computing Resources - 2017-09-14
Power and Sample Size Analysis with R - 2017-10-12
Python Web apps using the Flask framework - 2017-10-23
R Package Development Tools - 2017-10-16
Reproducible Reporting with R and RMarkdown - 2017-11-6
 

Spring 2017

Data Analysis, Visualization, and Computing Workshops

Coordinated under the UVA BioConnector branding, these workshops were led by SOM Research Computing, Health Sciences Library, Public Health Sciences, and the University Library

Advanced Data Manipulation with R - 2017-02-14
Advanced Data Visualization with R - 2017-02-21
Automated Image Analysis with ImageJ - 2017-03-29
Building Shiny Web Applications in R - 2017-04-18
Data cleansing in Python using Pandas and the Jupyter Notebook - 2017-03-15
Data visualization in Python using Matplotlib v. 2 and Bokeh - 2017-03-28
Essential Statistics with R - 2017-02-23
Introduction to Cloud Computing with AWS - 2017-04-04
Introduction to Python - 2017-02-09
Introduction to SAS - 2017-01-31
Introduction to the Command Line - 2017-01-26
Introduction to ArcGIS - 2017-03-27
Introduction to Dedoose - 2017-04-10
Introduction to SPSS - 2017-02-15
Managing Your Spreadsheet Data - 2017-03-14
Organizing Your Spreadsheet Data - 2017-01-24
Power and Sample Size Analysis with R - 2017-03-02
Python Web apps using the Flask framework - 2017-03-30
Quantitative analysis and visualization of medical images using Advanced Normalization Tools (ANTs) - 2017-04-19
R for Beginners - 2017-01-24
R for Beginners - 2017-02-02
Statistical Analysis with SAS - 2017-02-17
Survival Analysis in R with TCGA Data - 2017-03-31