ABI OMICSS Guide 2021
  • Welcome
  • Week 1
    • Molecular Biology
      • Introduction to Biology
      • Macromolecules
      • DNA & RNA
      • Cell Division
    • Command-Line
      • Connecting to the Server
      • The Linux Command-Line For Beginners
      • The Bash Terminal
    • R Programming
      • Getting Started
      • The Basics
      • Data Types
    • Week 1 Exam
  • Week 2
    • Molecular Biology
      • DNA Proofreading And Repair
      • Telomeres and Telomerase
      • Genes
      • The One Gene, One Enzyme Hypothesis
      • Transcription
      • Translation
    • R Programming
      • Data Types (continuation)
      • Reading Data
      • Subsetting
      • Control Structures
      • Functions
      • Scoping Rules
    • Week 2 Exam
  • Week 3
    • Molecular Biology
      • tRNA and Ribosomes
      • Stages of Translation & Protein Targeting
      • Heredity
      • Probabilities In Genetics
    • R Programming
      • Loop Functions
      • Base Graphics
    • Statistics and R
      • The Basics
    • Week 3 Exam
  • Week 4
    • Molecular Biology
      • Interesting Cases of Genes
      • The Chromosomal Basis of Inheritance
      • Variation in Species
      • Phenotype plasticity
    • R Programming
      • Practice 2
      • Practice 3
    • Statistics and R
      • Random Variables and Probability Distributions
      • Central Limit Theorem
    • Week 4 Exam
  • Week 5
    • Statistics and R
      • Confidence Interval
      • Introduction to Inference
      • t-distribution and Comparing Means
      • Linear Models
    • Experimental Techniques
      • Polymerase Chain Reaction (PCR)
      • Gel Electrophoresis
      • Sanger Sequencing
      • NGS Sequencing
    • Week 5 Exam
  • Week 6
    • Statistics and R
      • Power
      • ANOVA
      • Covariance and Correlation
    • NGS
      • Basic Unix Commands
      • Sequences and Genomic Features
      • FastQC
      • Practice Exercises
    • Week 6 Exam
  • Week 7
    • Statistics and R
      • Monte Carlo Simulation
      • Exploratory Data Analysis
      • Linear Regression
    • NGS
      • BEDtools
      • Alignment and Sequence Variation
      • Integrated Genomics Viewer
    • Week 7 Exam
  • Week 8
    • NGS
      • Variant Calling With GATK
      • Practice 1
    • Week 8 Exam
  • Module Syllabi
  • Additional Resources
  • Conclusion
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On this page
  • Enrolling in the Course
  • Install R and R Studio
  • Set Up swirl
  • Congratulations!

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  1. Week 1
  2. R Programming

Getting Started

This page takes an estimated 40 minutes to complete.

PreviousR ProgrammingNextThe Basics

Last updated 3 years ago

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The content of this module is offered by Johns Hopkins University.

Enrolling in the Course

1. Navigate to the course home page

2. Click on the Enroll button

3. Choose the "Data Science: Foundations using R Specialization" option.

4. Click "Next"

5. If you plan to study R beyond the scope of this guide, then feel free to proceed with the free trial initialization process and enter your financial credentials. If not, choose the "Audit course" option.

Install R and R Studio

Using the course resources, download and install R and R Studio on your machine. You can follow the below links for convenience.

For Mac users

For Windows users:

Set Up swirl

The swirl teaches you R programming and data science interactively, at your own pace, and right in the R console. We use swirl for practice problems.

To install it, follow the below steps.

1. Open RStudio and type the following into the console.

> install.packages("swirl")

2. This is the only step that you will repeat every time you want to run swirl. First, you will load the package using the library() function. Then you will call the function that starts swirl. Type the following, pressing Enter after each line:

> library("swirl")
> swirl()

Congratulations!

If you made it here, then congratulations! You have successfully completed this section. Move to the next portion of the guide with the arrow buttons below.

You can read more about swirl .

Install R on a Mac
Installing R Studio on Mac
Installing R on Windows
Installing R Studio on Windows
here
from this Coursera course