Skip to end of metadata
Go to start of metadata

You are viewing an old version of this content. View the current version.

Compare with Current View Version History

« Previous Version 30 Next »

General Information

During this 2-day workshop you will be learning the following:

    * R syntax

    * Data structures in R

    * Inspecting and manipulating data

    * Making plots to visualize data

    * Exporting data and graphics

In addition to the above, you will also learn about good data management practices, installing and working with data packages from various sources, and the different ways to get help when coding in R. 


Setup

Please install the following programs on the laptop you will be using in class:

  1. Rstudio (pick the appropriate Installer for your operating system).  
  2. R (pick the appropriate download for your operating system and choose the most recent version)

Schedule

******************************************** Day1 Schedule ********************************************

10:00 - 10:30

Introduction to course

Radhika

10:30 - 11:10

Intro to R and RStudio

Meeta

11:10 - 12:30

R syntax and data structure

Mary

12:30 - 13:30

Lunch 

13:30 - 14:15

Functions and arguments

Meeta

14:15 - 15:15

Data manipulation (Part 1) 

Radhika

15:15 - 15:25

Coffee 

15:25 - 17:00 

Data manipulation (Part 2)

Mary


******************************************** Day2 Schedule ********************************************
10:15 - 10:30

Refresher

All
10:30 - 11:05

Nested functions

Meeta
11:05 - 12:00

Matching and simple statistics

Mary

12:00 - 13:00

Lunch 
13:00 - 13:50

Matching and simple statistics

Mary
13:50 - 14:50

Data visualization with R

Radhika
14:50 - 15:00Coffee 

15:00 - 16:05 

Data visualization with R (cont.)

Meeta
16:05 - 16:15

Resources, wrap-up, questions

Radhika
16:15 - 17:00

Optional Exercises/Practice

All


Acknowledgements, Support & License:

These lessons have been developed by members of the teaching team at the Harvard Chan Bioinformatics Core (HBC). These are open access materials distributed under the terms of the Creative Commons Attribution license (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Some of the materials used in this lesson are adapted from work that is Copyright © Data Carpentry (http://datacarpentry.org/). All Data Carpentry instructional material is made available under the Creative Commons Attribution license (CC BY 4.0).

 


  • No labels