A workshop series on how to efficiently manage and analyze sequencing data. Bioinformatics Workshops

Introduction to R: Basics, Plots, and RNA-seq Differential Expression Analysis

At a glance
Opportunity for
  • Participants to understand the basics of R and RStudio and their application to differential gene expression analysis on RNA-seq count data
Eligibility
  • MD, DNP, PhD or equivalent, DDS/DMD
  • Receipt of endorsement from an applicant's supervisor stating the applicant will be able to attend all days of the workshop
  • Accepted applicants of the Introduction to UNIX and RNA-seq Analysis workshop will have priority admission
Time commitment
  • Three days
Funding level
  • Tuition-free
Resources
Session dates
  • November 1-3, 2017
Application Due
  • 5:00pm on September 6, 2017
  • Endorsements due 5:00pm September 11, 2017
Notifications
  • All applicants will be notified of their status via email no later than September 29, 2017.
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This three-day hands-on workshop taught by the teaching team at the Harvard Chan Bioinformatics Core will introduce participants to the basics of R and RStudio and their application to differential gene expression analysis on RNA-seq count data.

R is a simple programming environment that enables the effective handling of data, while providing excellent graphical support. RStudio is a tool that provides a user-friendly environment for working with R. Together, R and RStudio allow participants to manipulate data, plot, and use DESeq2 to obtain lists of differentially expressed genes from RNA-seq count data.

This workshop is intended to provide both basic R programming knowledge AND its application. Participants should be interested in:

  • using R for increasing their efficiency for data analysis
  • visualizing data using R (ggplot2)
  • using R to perform statistical analysis on RNA-seq count data to obtain differentially expressed gene lists

Workshop segments will address the following:

  • R syntax: Understanding the different 'parts of speech' in R; introducing variables and functions, demonstrating how functions work, and modifying arguments for specific use cases.
  • Data structures in R: Getting a handle on the classes of data structures and the types of data used by R.
  • Data inspection and wrangling: Reading in data from files. Using indices and various functions to subset, merge, and create datasets.
  • Visualizing data: Visualizing data using plotting functions in base R as well as from external packages such as ggplot2.
  • Exporting data and graphics: Generating new data tables and plots for use outside of the R environment.
  • Differential expression analysis for RNA-seq data:
    • QC on count data
    • Using DESeq2 to obtain a list of significantly different genes
    • Visualizing expression patterns of differentially expressed genes
    • Performing functional analysis on gene lists with R-based tools

It is strongly recommended that applicants accepted into the Introduction to R workshop also apply for and attend the September 2017 iteration of the Introduction to UNIX and RNA-seq Analysis workshop. The Introduction to R workshop will show participants how to use gene count data that was generated in the UNIX workshop to generate lists of differentially expressed genes.

The application for the Introduction to UNIX and RNA-seq Analysis workshop closes August 16, 2017, and accepted applicants of the UNIX workshop will have priority admission in Introduction to R: Basics, Plots, and RNA-seq Differential Expression Analysis. Space in this workshop is limited to 30 attendees. Participants will be accepted based on their application responses, eligibility, and application submission date.

Harvard Catalyst Postgraduate Education Program's policy requires full attendance and the completion of all activity surveys to be eligible for CME credit; no partial credit is allowed.

The Harvard Catalyst Education Program is accredited by the Massachusetts Medical Society to provide continuing medical education for physicians.