CBB Jamboree - Intro to R

Course Description

This course is designed for the Yale University Computational Biology & Bioinformatics (CBB) program's Jamboree. It provides a quick introduction to basic R commands while assuming familiarity with programming concepts. The majority of the course focuses on tidy data analysis using tidyr/dplyr and visualization using ggplot2

This course is designed for the Yale University Computational Biology & Bioinformatics (CBB) program's Jamboree. ...

Course Outline

1. 1

   Intro to basics

   In this chapter, based on DataCamp's Intro To R course, you will take your first steps with R. You will learn how to use the console as a calculator and how to assign variables. You will also get to know the basic data types in R. Let's get started!

   • 

     How it works

     100 xp
   • 

     Variable assignment

     100 xp
   • 

     Basic data types in R

     100 xp
   • 

     What's a data frame?

     100 xp
   • 

     Quick, have a look at your data

     100 xp
   • 

     A second look, data structure

     100 xp
   • 

     Slicing data frames

     100 xp
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2. 2

   Data the Tidy Way

   In this chapter, you will learn some of the fundamentals of taking raw data and cleaning it to form tidy data, the fundamental currency of data science and visualization tools such as ggplot2.

   • 

     Intro to Data Science

     0 xp
   • 

     Some (Un)Tidy Data

     0 xp
   • 

     A Tidy Sample

     0 xp
   • 

     Real (Messy) Data: Income Distribution by Religion

     100 xp
   • 

     Refactoring Columns Into a Variable

     100 xp
   • 

     Joining Multiple Data Sets

     100 xp
   • 

     Filtering Down To The Most Interesting Data

     100 xp
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3. 3

   Beautiful Data

   From tidy data comes great visualization - learn how to visualize your data using the grammer of graphics.

   • 

     Introduction to ggplot2

     0 xp
   • 

     The grammar of ggplot2

     0 xp
   • 

     Exploring ggplot2

     0 xp
   • 

     Adding New Aesthetics

     0 xp
   • 

     Refining our Aesthetics Layer by Layer

     0 xp
   • 

     Adding Additional Geometries

     0 xp
   • 

     When Layering, Order Matters

     0 xp
   • 

     A Spoonful of Color Makes the Plot Rock

     0 xp
   • 

     Theming our Plots

     0 xp
   • 

     The Tools for Beautiful Plots

     0 xp
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4. 4

   Application to Expression Data

   In this chapter, you will combine what you learned in the first three chapters to read in, tidy, and visualize gene expression data. Let's get started!

   • 

     Putting it all together

     25 xp
   • 

     Reading in the data

     25 xp
   • 

     ExpressionSet Objects

     100 xp
   • 

     Filter the Data

     100 xp
   • 

     Combine the data

     100 xp
   • 

     Tidy the data

     100 xp
   • 

     Join the data

     100 xp
   • 

     Plotting Gene Expression

     200 xp
   • 

     Plotting Gene Expression (2)

     200 xp
   • 

     Plotting Gene Expression (3)

     200 xp
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5. 5

   Extra Credit - Summarising Data

   Now at the end of our course, use what you know to take your data science investigations to the next level!

   • 

     Summarising Data

     0 xp
   • 

     Summarising Data (2)

     0 xp
   • 

     Summarising Data (3)

     0 xp
   • 

     Summarising Data (4)

     0 xp
   • 

     Summarising Data (5): Conclusion

     0 xp
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