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Training Update: March 16, 2020

As part of Harvard Medical School's response to COVID-19, HMS Research Computing is now working remotely.

All training classes will be held online until further notice, via Zoom meetings.

Registrations are now managed through the Harvard Training Portal, which requires an HUID. Those members of the extensive HMS community who do not currently have HUIDs - such as employees at affiliate hospitals, or collaborators from other institutions - may self-register for one as a "Person of Interest" with their faculty member's sponsorship. This form may take several days to process, and is available here: 

Spring 2021 (Part 2) Registration is open!

ClassDateTimeLocationSeatsMaterialRegistration (Only click here to register!)
R/Biostatistics Part I4/23/20211-3pVirtual48

R Biostatistics Files

Registration link

R/Biostatistics Part II4/30/20211-3pVirtual48R Biostatistics Files
R/Biostatistics Part III5/7/20211-3pVirtual48

R Biostatistics Files

R/Biostatistics description:

The HMS Research Computing R Biostatistics course is a three class, advanced instructional course covering the basics of RNA-seq analysis with Bioconductor and the R statistical programming language. Bioconductor provides tools for the analysis and comprehension of all types of high-throughput genomic data. Students should have a beginner's level of proficiency in R programming and an understanding of basic statistical principles before registering for the course.

The course covers standard supervised statistical approaches for the comprehensive analysis of a published Cancer Genome Atlas (TCGA) human breast cancer RNA-seq dataset. Topics include edgeR differential gene expression analysis and GOSeq functional enrichment analysis of gene ontology terms. Data visualization techniques are emphasized, and each two-hour class includes a lecture and R practicum. The third two-hour class includes a lecture on deep learning in the biomedical sciences. Course registration includes all 3 classes.

Comprehensively commented R scripts are provided to the student (R Biostatistics Files), as the objective of the course is to learn common biostatistical methods used for RNA-Seq analysis. Students are strongly encouraged to use personal laptops for the course.

To be prepared for the classes, students are encouraged to download and install the latest versions of R and RStudio prior to the first class.

RStudio -

Spring 2021 (Part 1) Registration is open!

MATLAB & Simulink Spring 2021 Webinar Series

Please join us for the following spring series of live webinars. We hope you find the information helpful for both teaching and research activities. The series is open to all faculty, researchers and students. We look forward to your attendance.



February 3rd

Introduction to MATLAB


February 17th

Using MATLAB with Python


March 3rd

21 MATLAB Features You Need Now


March 24th

Machine Learning with MATLAB


April 7th

Systems Modeling and Controls with Simulink & Simscape


April 21st

What’s New in MATLAB for Research


May 5th

Distance Learning and Virtual Labs



Important Notice: After registration, you should receive an confirmation email from the Harvard Training Portal with a Zoom link. If you do not have your email address on file in the Training Portal, such messages cannot be be sent to you. Please contact us for the Zoom meeting details if you did not get a confirmation email.

ClassDateTimeLocationSeatsTraining MaterialsRegistration (Only click here to register!)
Intro to O2Wednesday, February 3, 20213-5pmVirtual30User Training githubRegistration link
Intro to PythonWednesday, February 10, 20213-5pmVirtual30User Training githubRegistration link
No classWednesday, February 17, 2021

Intro to MatlabWednesday, February 24, 20213-5pmVirtual50User Training githubRegistration link
Intro to Git + Github (moved to next week)Wednesday, March 3, 20213-5pmVirtual30User Training githubRegistration link
Intro to Git + GithubWednesday, March 10, 20213-5pmVirtual30User Training githubRegistration link
No classWednesday, March 17, 2021

Intermediate O2Wednesday, March 24, 20213-5pmVirtual30User Training githubRegistration link
Intro to PythonWednesday, March 31, 20213-5pmVirtual30User Training githubRegistration link
Intro to Parallel ComputingWednesday, April 7, 20213-5pmVirtual50User Training githubRegistration link
Intro to RWednesday, April 14, 20213-5pmVirtual30User Training githubRegistration link
Intro to O2Wednesday, April 21, 20213-5pmVirtual30User Training githubRegistration link
No classWednesday, April 28, 2021

No classWednesday, May 5, 2021

Intro to PythonWednesday, May 12, 20213-5pmVirtual30User Training githubRegistration link
Introduction to Globus Data Transfer and Data Collaboration on O2Wednesday, May 19, 20213-5pmVirtual30User Training githubRegistration link
Intro to RWednesday, May 26, 20213-5pmVirtual30User Training githubRegistration link
Intro to O2Wednesday, June 2, 20213-5pmVirtual30User Training githubRegistration link

Intro to O2

O2 for New Users addresses the needs of users who have very little linux experience, and are just getting started with HPC. More time will be devoted to covering linux basics, and the concepts of schedulers and jobs, and data management best practices. The lecture portion of this class is one hour, the second hour will be spent clinic-style with HMS RC staff to address workflow-specific questions and help convert commands to O2 SLURM syntax.

Intro to Python

Python is a popular scripting language for scientific computing and available across all computer platforms. The course will introduce you to some of the basics of the Python language as well as some of the nuances involved with its use specific to the O2 environment. The goal is to provide users with a foundational level of familiarity. Topics covered include basic data types and declaration, flow control (if/else), loops, a brief introduction to constructing a script, and a briefer introduction to modules. The course will be taught on O2, but general concepts are easily translatable to desktop and local installations.

Intro to R/Bioconductor

Intro to using R and Bioconductor. R is a powerful, open-source, highly adaptable statistical language useful for crunching numbers to datasets like those produced by next-gen sequencing. This class covers R basics and learning to think like/understand R. Users will learn how to set up personal R libraries on O2, and use O2 R for its high memory allocations and parallelization. Topics include how to install packages, learn about variables, data types. data manipulation, flow control, and functions, perform simple statistical tests, and create a variety of plots. Laptops are encouraged.

Class Files Here

Intro to MATLAB

Matlab has become the “language of science” in the past few decades. It is simple to use, yet powerful enough to be productive on large computing infrastructures. If you need: 1) Fast prototyping of research ideas; or 2) avoid spending too much time in coding instead of doing real science by taking advantage of Matlab’s built-in functions; 3) User friendly graphical interface and educational documentation; 4) Simplicity of code; 5) Easy access to GPU computing power; 6) Easy plotting and presentation of data; you will find this introduction course useful. This course will introduce the basics of the MATLAB coding language with O2-scalability and data presentation.

Intro to Parallel Computing

This is a short introduction to Parallel Computing that will include an overview of the basic concepts of parallel programming: from running your job in an embarrassingly parallel way to writing simple shared and distributed memory parallelization codes in different languages. The seminar will cover several examples of actual parallel codes however it will not have any "hands on" components. A basic programming experience (of any language, no parallelization) is preferred in order to better follow the topics presented during the seminar.

Intermediate O2

Intermediate O2 is for current O2 users who would like to brush up on their bash skills, learn more advanced file transfer techniques, and unleash some of the powerful features of the SLURM scheduler.

Intro to Git and GitHub

This course introduces Git and GitHub and covers topics including: Getting Started with Git for version control, Using GitHub Desktop effectively, Collaborating with others on GitHub, and Utilizing GitHub Flow for better workflow. No previous exposure is assumed. We hope attendees will leave the class with the knowledge and tools necessary to start integrating Git into their workflows and excited to begin collaborating on GitHub.

Introduction to Globus Data Transfer and Data Collaboration on O2


Additional computational trainings are available through other groups:

Please reach out directly to the above groups if you are interested in attending their trainings.

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