Becker Library offers free trainings to the Washington University Medical Center community on a variety of research computing topics, including:
- Computing Basics
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.
These webinars are for those with no prior experience with programming languages. Registration is required to receive a Zoom link. Click on the session title below to register for one or all sessions.
Join us to learn about the R programming language, R data objects, and basic R code for some common data analysis tasks. A small example dataset will be used to demonstrate data exploration, manipulation, and visualization using built-in functions available in base R.
Join us to learn about the Python programming language and Python code for some basic data analysis tasks. Popular Python libraries used for data exploration, manipulation, and graphing on data frames will be introduced.
Becker Library worked with Research Infrastructure Services (RIS) to offer these virtual workshops, designed for those without any prior experience using the Unix Command Line Interface (CLI) and High Performance Computing (HPC).
All Computing Basics workshop materials can be found here.
Submitting Jobs to RIS Scientific Compute Platform – 11/30/2023
This workshop introduced basic commands for submitting jobs to RIS Scientific Compute Platform’s queuing system. Attendees learned to use queue system commands and docker images to submit jobs to the queue in both interactive and non-interactive modes.
Software Applications Used in High Performance Computing Environments – 11/16/2023
This workshop introduced text editors, shell and batch scripts, Docker container technology, and the ssh protocol. Attendees learned how to write, edit and run shell scripts, how to create a simple Docker container, and how to connect to RIS Scientific Compute Platform.
The Unix Shell and Command Line Basics – 11/9/2023
This workshop introduced the Unix command line interface, the Unix file system, and basic Unix commands. Attendees learned how to create, explore and manage Unix files and folders.
Open On Demand on RIS Scientific Compute Platform – 11/2/2023
Open On Demand (OOD) is a web-based interface for remote computing. OOD provides a web browser interface for users to connect to and interact with RIS compute resources, and access a variety of software for running jobs on the RIS Scientific compute platform. In this workshop, attendees will learn how to run jobs using OOD on RIS scientific compute platform.
Single-Cell RNA-Sequencing (scRNA-Seq) Data Analysis Using R and RIS Compute Platform – 9/28/2021
This workshop was offered by Becker Library, the Institute for Informatics and Research Infrastructure Services (RIS), and discussed analyses of scRNA-Seq data using R on the RIS Scientific Compute Platform. Attendees learned how to create and use a Docker container image for scRNA-Seq data analysis to submit a job that sets up RStudio on the RIS Scientific Compute Platform. Finally, R packages were used to explore and visualize the data. All the workshop materials are here
These MATLAB webinars were organized in collaboration with WUIT’s Research Infrastructure Services (RIS) and were led by MathWorks Engineers. See below for a description of each workshop and links to the workshop materials.
Medical Image Analysis and AI Workflows in MATLAB – 5/23/2023 at 10 AM
MATLAB provides tools and algorithms for end-to-end medical image analysis and AI workflows – I/O, 3D visualization, segmentation, labeling and analysis of medical image data. This webinar introduces the Medical Imaging Toolbox for MATLAB. Medical images come from multiple sources such as MRI, CT, X-ray, ultrasound, and PET/SPECT. The challenge is to visualize and analyze this multi-domain image data to extract clinically meaningful information and conduct other tasks such as training AI models.
This webinar shows the complete medical image analysis workflow for AI applications. You will learn how to import, visualize, segment and label medical image data, and utilize these data in AI model training.
- Importing and visualizing multi-domain DICOM medical images
- Segmenting and labeling 2D and 3D radiology images
- Designing and training AI and deep learning models
Webinar slides are located here
The recording of the 5/23 webinar didn’t work, but here is a recording of the same webinar that you can view any time
Machine and Deep Learning for Medical Imaging with MATLAB – 3/29/2022 at 2 PM
In this session, attendees learned AI techniques that are increasingly seen as powerful tools to address many complex problems. The lecture explored in detail the workflow involved in developing and adapting machine and deep learning algorithms for medical image classification or segmentation problems using real-world case studies. Some of the tasks explored in this workflow are:
- Import and manage large sets of images without loading them into memory
- Build networks from scratch with a drag-and-drop interface of Deep Network Designer
- Perform classification tasks on images, and pixel-level semantic segmentation on images
- Semi-automate ground-truth labeling efforts to increase training dataset
- Understand hyperparameter tuning and why it’s important.
Webinar slides are located here.
Additional Deep Learning webinar recordings can be accessed from here.
Parallel Computing with MATLAB – 3/25/2021 at 10 AM
Using the Parallel Computing capabilities in MATLAB allows users to take advantage of additional hardware resources that may be available either locally on their desktop or on clusters, clouds, and grids. By using more hardware, you can reduce the cycle time for your workflow and solve computationally and data-intensive problems faster. This webinar discussed a range of workflows available to scale MATLAB applications with minimal changes to your MATLAB code and without needing to learn low-level programming. Below are some of the highlights discussed:
- Leveraging multiple cores or CPUs
- Working with high-level constructs—parallel for-loops, special array types, and parallelized numerical algorithms.
- Scaling up to utilize clusters, grids, and clouds
- Utilizing tall and distributed arrays to work with large data sets
- Using MATLAB for GPU computing
NOTE: MATLAB is accessible on WUIT’s RIS compute cluster. You can request access to RIS compute and storage to leverage MATLAB, to do so, use your WUSTL key to log in here (All WashU Faculty have access to 5TB of free storage available to them). Please visit the RIS website to learn more.
Workshop recording and other materials are located here.
Image Processing Made Easy Using MATLAB – 3/25/2021 at 1 PM
Image processing is the foundation for building vision-based systems based on cameras and frame grabbers. You might have a new idea for using your camera in the fields of engineering, sciences, biomedical, or oceanography, for example, and are not sure where to start. This webinar focussed on several key workflows to make things easy and help get you started. The real-world examples presented were focused on:
- Pre-processing images using enhancement and filtering techniques
- Separating objects of interest using segmentation techniques
- Testing your algorithm on large sets of images
Some highlights discussed during the webinar include:
- MATLAB help documentation and examples help with getting started quickly
- Interactive apps and live scripts enable exploration of different techniques
- Extensive library of built-in image processing algorithms
Workshop recording and other materials are located here.
Using Python for Basic Data Visualization – September 2023
This workshop introduced three popular libraries used for data visualization in Python. Attendees learned how to create and customize simple Python plots using the Matplotlib, Seaborn, and Plotly Express libraries. Workshop materials and a recording of the workshop can be found here.
Using Python for Basic Data Exploration and Manipulation – September 2023
This workshop introduced the Python programming language. A practice dataset was used to demonstrate the import, exploration & manipulation of data from a dataframe using the Pandas library. Workshop materials and a recording of the workshop can be found here.
Basic Data Analysis Using Python – February 2021
This Love Data Week workshop introduced popular libraries for data analysis in Python and demonstrated common data analysis tasks including data import, exploration & manipulation using the Pandas library as well as data visualization using the Matplotlib, Seaborn, and Plotly Express libraries. The hands-on exercises were presented in Jupyter Notebook. All the workshop materials can be found here.
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. This Love Data Week virtual workshop will provide an introduction to using advanced data visualization techniques in R. The workshop materials can be found here
RNA-seq Data Analysis Using Bioconductor – 9/12/2023
This workshop was taught by Madhurima Kaushal, Senior Bioinformaticist at the Institute for Informatics Data Science and Biostatistics (I2DB). The session provided an introduction to using R and Bioconductor for RNA-seq data analysis. We used 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 learned from hands-on activities. The workshop materials are located here.
Introduction to 16S Amplicon Sequence Variant Analysis using R – 7/20/2023
This hybrid workshop was presented by Dr. Brigida Rusconi, an Instructor in the Department of Pediatrics at Washington University School of Medicine. The workshop introduced common 16S metrics and good practices for 16S data analysis. Attendees learned how to use RStudio docker images with pre-installed packages and scripts to analyze a mock 16S V4 data set. All workshop materials and a recording are found here.
Introduction to R Workshops – January/February 2023
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 – Data Visualization in R Using ggplot2 – 2/23/2023
This workshop introduced how to install, load and manage R packages, and demonstrated how to use the ggplot2 package to create and customize basic plots in R.
Introduction to R – Bioconductor – 2/7/2023
This workshop introduced Bioconductor and covered installing, loading, and managing Bioconductor packages as well as basic genomic data exploration using the VariantAnnotation package.
Introduction to R – Data Visualization Using R base – 1/24/2023
This workshop introduced data visualization in R and demonstrated how to create and customize basic plots using the built-in functionality in base R.
Introduction to R – Data Exploration and Manipulation Using R base – 1/17/2023
This workshop introduced R data objects and functions, basic data exploration, manipulation, and visualization, all using the built-in functionality in base R.
Single Cell Data Analysis Using R – 11/17/2022
This interactive workshop was led by a Bioinformatics Scientist at the Institute for Informatics and was focused on using R for Single Cell RNA Sequencing (scRNA-seq) data analysis with live demonstrations on how to analyze and interpret scRNA-Seq data using the R package Seurat. The workshop recording and additional materials are located here
Advanced Data Visualization and data wrangling in R – 2/18/2022
This Love Data Week virtual workshop was led by a Bioinformatics Scientist at the Institute for Informatics and introduced advanced data visualization techniques in R. Attendees had an opportunity to learn common data wrangling and data visualization methods using the tidyverse package collection in R. The workshop materials can be found here.
Visualization of COVID-19 Data Using R – 11/2/2021
This workshop was led by a Bioinformatics Scientist from the Institute for Informatics (I2) and explores the structure of publicly available COVID-19 data and methods to visualize the data with the aim to understand disease epidemiology. The R code for this session can be found in this RStudio Cloud Project. All workshop materials are located here.
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.
- Computational Biology and Bioinformatics Resources – Directory for bioinformatics analysis and collaboration (must be connected to the WashU network or VPN).
- Bioinformatics Workshop series – Free yearlong bioinformatics training (BFX) that occurs on campus and is open to anyone interested in learning best practice methods, programming, technology, and genomic data analysis. Lectures are recorded and participants can join anytime throughout the year.
- O’Reilly Online Learning platform – follow the steps outlined in this blog to search for learning materials on a variety of research computing topics.
- LinkedIn Learning – search for thousands of on-demand videos on a variety of topics including research computing topics, available at no cost to everyone in the WashU community.