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CBB Jamboree - Intro to R
- 1 hour
- 0 Videos
- 39 Exercises
- 32 Participants
- 2,250 XP
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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
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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!
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3
Beautiful Data
From tidy data comes great visualization - learn how to visualize your data using the grammer of graphics.
-
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!
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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.
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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!
-
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!
-
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.
-
3
Beautiful Data
From tidy data comes great visualization - learn how to visualize your data using the grammer of graphics.
-
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!
-
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!
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Stefan Avey
Instructor
Bioinformatics PhD Candidate at Yale University passionate about data science and data visualization in HealthTech and EdTech
Robert Amezquita
Instructor
PhD Candidate at Yale University Dept. of Immunobiology, with a fondness for (epi)genomics, cooking, dogs, biking, and Rocket League.