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Introduction to R

Introduction to R

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 ************************************
09:00 - 09:30

Introduction to course

Radhika
09:30 - 10:10

Intro to R and RStudio

Meeta
10:10 - 10:45

R syntax and data structure

Mary
10:45- 10:55Coffee 
10:55 - 11:40

R syntax and data structure (contd.)

Mary

11:40 - 12:40

Lunch 
12:40 - 13:25

Functions, arguments, packages and seeking help

Meeta
13:25 - 14:25

Data wrangling: vectors and factors 

Radhika
14:25 - 14:35Coffee 
14:35 - 16:00

Data wrangling: matrices, data frames and lists

Mary


************************************ Day2 Schedule ************************************
09:00 - 09:15

Refresher

All
09:15 - 10:15

Matching

Meeta
10:15 - 10:30Coffee 
10:30 - 11:00

Matching (contd.)

Mary
11:00 - 11:45

Data visualization with R

Radhika

11:45 - 12:45

Lunch 
12:45 - 13:30

Data visualization with R (contd.)

Radhika
13:30 - 13:45

Resources, wrap-up, questions

Radhika
13:45 - 14:00Coffee 
14:00 - 16:00

In-class Exercises/Practice

(Answer Key)

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).

 


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