Research Computing

Becker Library offers free trainings to the Washington University Medical Center community on a variety of research computing topics, including:

  • Computing 101
  • MATLAB
  • Python
  • R

These workshops are meant to serve as an introduction to research computing basics and prepare participants for ongoing learning. Check below to see what’s coming up or sign up for the mailing list to be notified each time a new workshop is scheduled.

Sign up for the mailing list

Contact Maze Ndukum (ndukummaze@wustl.edu) or Marcy Vana (vanam@wustl.edu) with any questions.

Upcoming Workshops

Several workshops are coming up in October (see dates below). Each workshop topic is offered on two consecutive dates and will be presented live via Zoom. The same content will be presented on both dates, so please choose the date that works best for you. Registration is required to receive a Zoom link.

R vs. Python – Love Them Both?10/1/2020 and 10/15/2020 (choose one date only, the same content will be offered on both dates)

This virtual hands-on workshop will introduce common data analysis tasks in the R and Python programming languages and explore which language is better suited for a particular task. Basic workflows and code for data manipulation and visualization will be explained using interactive web-based environments for R/RStudio and Python. Basic proficiency in R and/or Python is recommended.

Introduction to R – Genomic Data Analysis Using Bioconductor 10/8/2020 and 10/22/2020 (choose one date only, the same content will be offered on both dates)

This virtual workshop will provide an introduction to using R and Bioconductor for computational genomics. We will use the EdgeR and ShortRead packages to perform RNA sequencing data analysis, introducing various data formats, data input and output, data analysis and visualization. The attendees will also get an opportunity to learn from hands-on activities.

View a comprehensive list of Library classes and workshops

Previous Workshops

These workshops were offered in collaboration with the Center for High Performance Computing (CHPC) and were geared toward researchers new to high performance computing and the command line interface. During each workshop session, important background concepts related to computing were introduced in a simple presentation format, followed by hands-on exercises. While these workshops were focused on using the CHPC, the knowledge gained could be applied to other computing environments. The materials from these workshops can be found here.

#1 Tools to Connect and Move Data & Getting Around the Linux Command Line Interface – 3/26/19

Goals: to develop a basic understanding of the tools needed to connect to the CHPC and transfer data back and forth, and become familiar with the Unix file system and basic Unix commands

#2 Text Editors and Shell Scripts – 4/2/19

Goals: to gain knowledge of some of the options for text editors and learn how to write and execute basic shell scripts

#3 Running Jobs on the CHPC Cluster – 4/9/19

Goal: to learn how to write and submit batch scripts to run applications on the CHPC cluster

These MATLAB training sessions were organized in collaboration with the Center for High Performance Computing (CHPC) and were led by MathWorks Engineers. See below for a description of each workshop and links to the workshop materials.

Image Processing for Medical Applications Using MATLAB – 5/3/2018

This MATLAB training seminar included the following topics:

  • Analyzing medical images using MATLAB Apps
  • Image thresholding
  • Finding ROI properties
  • Automating your workflow with MATLAB

Workshop slides and other materials can be found here.

Demystifying Deep Learning: A Practical Approach in MATLAB – 5/14/2019

This seminar discussed MATLAB features that make it easy to:

  • Manage extremely large sets of images
  • Visualize networks and gain insight into the black box nature of deep networks
  • Perform classification and pixel-level semantic segmentation on images
  • Import training data sets from networks such as GoogLeNet and ResNet
  • Import and use pre-trained models from TensorFlow and Caffe
  • Speed up network training with parallel computing on a cluster
  • Automate manual effort required to label ground truth
  • Automatically convert a model to CUDA to run on GPUs

Workshop slides and other materials can be found here.

Parallel and GPU Computing with MATLAB – 5/14/2019

This hands-on workshop was focused on using MATLAB on the CHPC cluster. The following topics were discussed:

  • Toolboxes with built-in algorithms for parallel computing
  • Creating parallel applications to speed up independent tasks
  • Scaling up to computer clusters, grid environments or clouds
  • Employing GPUs to speed up your computations

Workshop slides and hands-on exercises can be found here.

These workshops were offered in collaboration with the Center for High Performance Computing and Institute for Informatics and were geared toward researchers new to programming and Python. Each workshop started with a 30-minute presentation covering important background information and then the remaining 90 minutes was devoted to hands-on activities.

Introduction to Python #1 – Getting Started with Python – 9/25/19 and 9/26/19

Goals: to develop a basic understanding of the Python programming language and to run basic Python code in the interactive Python environment, Jupyter Notebook

Previous workshop slides and hands-on activities

Introduction to Python #2 – Using Python for Data Analysis – 10/2/19 and 10/3/19

Goals: to learn to write Python code to perform data analysis and visualization, and create a Python virtual environment on a remote system

Previous workshop slides, hands-on activities, and data (weather_data_newyork, snow_data)

Introduction to R Zoom Workshops – September 2020

These virtual workshops were geared toward researchers new to programming and R. During each session important background concepts were introduced in a simple presentation format, followed by hands-on exercises. The workshop materials can be found here.

Introduction to R

This workshop introduced R data objects and functions, basic data exploration, manipulation, and visualization, all using R base.

Introduction R – Data Visualization in R Using ggplot2

This workshop introduced R packages and covered installing, loading and managing R packages as well as basic data visualization using the ggplot2 package.

Introduction to R – Bioconductor

This workshop introduced Bioconductor and covered installing, loading and managing Bioconductor packages as well as basic genomic data exploration with the VariantAnnotation package.

 

R vs. Python – Love Them Both? – October 2020

This workshop was offered by WashU’s Institute for Informatics, University Libraries and Becker Medical Library on Zoom. The workshop introduced some common data analysis tasks in the R and Python programming languages and explored which language is better suited for a particular task. During the hands-on portion of the workshop, basic Python and R code were explained using the interactive web-based environments, repl.it and RStudio Cloud respectively. The workshop materials are located here.

 

Genomic Data Analysis Using Bioconductor – October 2020

This workshop was offered by WashU’s Institute for Informatics, University Libraries and Becker Medical Library on Zoom. This virtual workshop provided an introduction to using R and Bioconductor for computational genomics. EdgeR and ShortRead packages were used to perform RNA sequencing data analysis, introducing various data formats, data input and output, data analysis and visualization. During the hands-on activities, R code was explained using the interactive web-based environment, RStudio Cloud. The workshop materials are located here.