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COVID-19 Research Resources
A curated list of research resources around guidelines, policies, and procedures related to COVID-1, drawn from Harvard University, affiliated academic healthcare centers, and government funding agencies

COVID-19 Research Resources
A curated list of research resources around guidelines, policies, and procedures related to COVID-1, drawn from Harvard University, affiliated academic healthcare centers, and government funding agencies

Calendar

Workshop: Introduction to RNA-seq Analysis Using High-Performance Computing and R

Deadline: Friday, September 14, 2018
Harvard Chan Bioinformatics Core

Workshop: Introduction to RNA-seq Analysis Using High-Performance Computing R- 09/14/2018

Session Dates: October 31-November 2 & November 14-16, 2018
Application Deadline: September 14, 2018

This six-day hands-on workshop series is led by the teaching team at the Harvard Chan Bioinformatics Core and includes the following two workshops:
Introduction to RNA-seq Analysis Using High-Performance Computing Workshop (3 days)
Introduction to R: Basics, Plots, and RNA-seq Differential Expression Analysis Workshop (3 days)
Applicants will submit one application for both workshops. Admitted participants must attend both workshops in full; no partial attendance is allowed.
Please note that these workshops do not cover single cell analysis and do not review personal data.

High-throughput sequencing techniques can rapidly provide a global picture of the processes within cells, allowing for accelerated discoveries in biology. As sequencing technologies improve and the costs decline, learning how to analyze and handle these large datasets has become imperative for researchers in biology and medicine.

In the Introduction to RNA-seq Analysis Using High-Performance Computing Workshop, participants will learn the basics of Unix/Linux and gain experience using the HMS compute cluster (O2).

The Introduction to R: Basics, Plots, and RNA-seq Differential Expression Analysis Workshop will show participants how to use gene count data generated in the previous workshop to generate lists of differentially expressed genes and perform functional analysis on them to gain better biological insight.

Please see the workshop website for complete information.

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