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Itmat pcbi-r-course-1


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First part of 3-part course on teaching the R statistical package.

First part of 3-part course on teaching the R statistical package.

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  • Exercise 1: Use the sequence function to 1:20 by 2Exercise 2: Use rep() to create a vector with a sequence of number from 1 to 3, repeated three timesExercise 3: Create a vector 1:10 with 3 consecutive repeating values (e.g. 1 1 1 2 2 2 … 10 10 10 )
  • Changing the data type of a single element changes the type of the rest of the elements.The one exception to this is “missing values” represented by the special constant “NA”. See example above
  • Transcript

    • 1. Intro to using R for Bioinformatics: Part 1 : The Basics
      Angel Pizarro
    • 2. Injecting a bit of reality
    • 3. Taking it a bit further…
      Waxing floors is not fun, and may not seem relevant, but have some faith Daniel-san
    • 4. Outline
      We will teach you some basic uses of R
      “Do & Tell” method where you will be asked to do an exercise and once done, we will explain what just happened.
      Will cover basics, plotting and microarray analysis
      We will not teach you statistics.
    • 5. What is ?
      R is a language and environment for statistical computing and graphics.
      You can do stuff like this
    • 6. Install & Run R
      You should have already installed R, but if you had trouble please see us after class
      Start R
      On Windows, use Tinn-R
      On Mac, use the source R application
      On Linux, use the console
    • 7. Help is plentiful
      Help in three ways
      Too much! Get me out!
    • 8. More Help
      Start an HTML help session
      Looks up the mean() function's help page
      Displays all help pages that contain text “mean”
    • 9. Whet your appetite…
    • 10. The Basics
      Please enter each of the following lines into your R session:
    • 11.
    • 12.
    • 13.
    • 14. Basic Algebra
      You will also see this form:
    • 15. Variables
      “x” and “y” are variables.
      They are pointers to some value
      They can also be pointers to some function
    • 16. Vectors
      Enter this in your session:
    • 17. Small tangent: What is “c (1,2,3)”?
      Use the help()
    • 18. Accessing Vector Members
      In R, Vectors start indexes at 1. Most programming languages start indexing at zero
      Also, NOT WHAT YOU THINK IT IS! It is a INDEX VECTOR, meaning that you access the members of a vector with a vector
    • 19. Small Tangent 2: Creating Sequences
      Create regular sequences using a colon
      Colon has high operator precedence
      Also see the seq() function
    • 20. Vectors
      Are a list of items of the same data type
      Short for “double precision floating point number”
    • 21. Doing Stuff with Vectors
      Math operations occur on each element in sequence
      Returns a vector of the same size
    • 22. Factors
      Simply a vector of items that mean something
      Disease classifications, drug dosage, US states, months, hapmap ethnic group
      Can be ordered
      Can have multiple levels
      GO Functions
    • 23. Array and Matrix
      Multi-dimensional generalizations of vectors
      k-dimensions where k > 0
      Assigned by the dim attribute
      Can be indexed by two or more indices
      If a single index value (can be a vector) is given, then dim is ignored and underlying vector values are accessed directly
      Unless the given index values is also an array
      Matrix is a two-dimensional array
    • 24. Example
    • 25. List
      An ordered collection of named components
    • 26. List Access
    • 27. Data Frame
      Bastard step child of List and Matrix
      Essentially a list of vectors of same length
      Closest representation to an Excel file in R
      Easiest way to make one is to read in a CSV file
    • 28.
    • 29.
    • 30. Functions
      We’ve already used them
      Functions take in arguments and perform some action using those arguments.
      Actions do not affect the input arguments
    • 31. Example
    • 32. Write to CSV file
      Extra column of the row indices
    • 33. Save your work!
      R keeps track of your data and functions
      You can start from where you left off if you save these to some file
    • 34. Start from your save point