Statistics for Biologists: Practicals

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1 Statistics for Biologists: Practicals Peter Stoll University of Basel HS 2012 Peter Stoll (University of Basel) Statistics for Biologists: Practicals HS / 22 Outline Getting started Essentials of the R Language Reading Data into R More fancy GUIs Peter Stoll (University of Basel) Statistics for Biologists: Practicals HS / 22

2 Getting started Download and install R Statistics for Biologists: Practicals HS / 22 Getting started Download and install R Statistics for Biologists: Practicals HS / 22

3 Getting started Running R R s Console (basic input/output device) after R has been started. Statistics for Biologists: Practicals HS / 22 Getting started Command Line The command line starts with a prompt (>) after which you can type commands 1. For example > help.start() > n <- 10 # assign 10 to scalar n Moreover, the command line is actually a mini editor and commands can be recalled (up-arrow), edited (ctrl-a, ctrl-e) and re-executed by hitting the Return key. Of course, the Introduction to R help page can also be called directly: 1 Note: Everything after # is treated as comment and is not executed Statistics for Biologists: Practicals HS / 22

4 Getting started Typesetting To improve readability we use distinct typesetting. Input R code such as the command n <- 5 or d <- data.frame is typeset in Courier. Longer sections of code are shown as blocks of command, mimicking the R console (i.e. also including the command prompt > at the beginning of the line): > n <- 5 # a scalar (single number) > x <- 1:n # a vector of numbers > char <- letters[1:n] # a vector of characters > d <- data.frame(x,char) # a data.frame combining numbers and characters > d x char 1 1 a 2 2 b 3 3 c 4 4 d 5 5 e The Output produced by R in the Console is again Courier, but black. Statistics for Biologists: Practicals HS / 22 Getting started Special characters Name char meaning Number sign: # used for comments Dollar sign: $ used to index columns of data frames Parenthesis: (...) arguments of functions Brackets: [...] used to index vectors Braces: {...} control structures (e.g. if, loop) Circumflex: to the power of (e.g. 4 2 ) Tilde: specification of statistical model Ampersand: & logical AND Vertical bar: logical OR Exclamation:! logical NOT Percent sign: % %*% matrix multiplication Some often used special characters Statistics for Biologists: Practicals HS / 22

5 Essentials of the R Language R is essentially a programming language and environment for Data handling and management Graphical representation Statistical analysis The language is case sensitive (a!= A) and elementary commands 2 consist of Assignments (> n <- 10) evaluated passed to variable not automatically printed Expressions (> 2 + 3) evaluated result printed value lost 2 if a command is not completed at the end of a line, R will give a different prompt (+) Statistics for Biologists: Practicals HS / 22 Essentials of the R Language Scalars and Variables We can define scalars (single value) and variables or vectors (multiple values) and assign values in various ways. Some simple examples: > n <- 10 # an assignment > n # request output [1] 10 > x <- 1:n > x [1] > y <- x # another asignment > i < # an assignment using an expression > i [1] 5 Statistics for Biologists: Practicals HS / 22

6 Essentials of the R Language Factors Factors are also very useful as we will see later. > f <- factor(rep(1:2,each=n/2),labels=c("treatment","control")) > f [1] treatment treatment treatment treatment treatment control control [8] control control control Levels: treatment control Use help to find out what the function rep does and how exactly it is used to define the factor f. Statistics for Biologists: Practicals HS / 22 Essentials of the R Language Data frames Variables and factors can be combined to compact structures called data frames. > d <- data.frame(x,y,f) > d x y f treatment treatment treatment treatment treatment control control control control control Statistics for Biologists: Practicals HS / 22

7 Essentials of the R Language Housekeeping A couple of functions to show, clean and maintain your workspace. Use help to get a description of their arguments and try them out. > getwd() # get the working directory > dir() # list files in working directory > ls() # list objects in R's working space > rm() # remove obejcts from working space We will see later that R Studio incorporates most of these commands in it s windows and menues. Statistics for Biologists: Practicals HS / 22 Essentials of the R Language R Scripts Of course, it would be tedious and cumbersome to always work interactively at R s console. A more convenient way to work is with R Scripts. An R Script is a simple text file containing R commands and comments. An R script has big ADVANTAGES. It is a RECORD OF YOUR WORK! permanent repeatable annotated and hence documented cross-platform sharable R scripts can be written in any text editor. Some are more fancy than others and many provide additional functionality (e. g. colored syntax highlighting, check of parenthesis). Some examples: R Studio (will be introduced shortly) Tinn-R (another Tool providing context sensitive editing) R Commander (An R package providing a Graphical User Interface or GUI for statistical analyses) Statistics for Biologists: Practicals HS / 22

Essentials of the R Language R Scripts Before we start looking at the more fancy script editors, we use R s built in script editor to write our first script 3.

.. create new folder Statistics for Biologists (or just Work ) Save your R script Change Working directory to the name of the new folder I will go through the steps and show you how to execute the

8 Essentials of the R Language R Scripts Before we start looking at the more fancy script editors, we use R s built in script editor to write our first script 3. Here s how to do it: Start R use File menue to open a new script write some initial comments using # Comment... write some R commands use File menue Save as... create new folder Statistics for Biologists (or just Work ) Save your R script Change Working directory to the name of the new folder I will go through the steps and show you how to execute the script. Use the following overview of R s GUI with the different windows for your annotations. 3 Mac users will have line numbers and syntax highlighting. PC users don t. Statistics for Biologists: Practicals HS / 22 Essentials of the R Language R Scripts can be executed in different ways 1.) line by line (ctrl-r), usefull for debugging (i.e. find errors) 2.) from the console by using function source(file="file name",echo=true) Note: The script will NOT RUN without producing errors. Exercise: Find the errors, correct them and execute the script. Statistics for Biologists: Practicals HS / 22

9 Reading Data into R Read table Data will usually be read from ordinary text files. > data <- read.table(file="raw_data_1.txt",header=true) > head(data) # check that we read the file we wanted indep dep factor treat treat treat treat treat contr > str(data) # inspect what the structure data contains 'data.frame': 10 obs. of 3 variables: $ indep : int $ dep : num $ factor: Factor w/ 2 levels "contr","treat": Unfortunately, many things can go wrong! Statistics for Biologists: Practicals HS / 22 Reading Data into R Error correction Some important RULES: Names of variables should be single strings without spaces Factor levels should also be single strings without spaces There should be no empty cells... Exercise: You will be given similar files, but with errors or inconsistencies that prevent correct reading into R. Try to understand the error messages that the command read.table produces. Correct the problem by editing the data files and try again. Statistics for Biologists: Practicals HS / 22

More fancy GUIs R Studio R Studio (http://rstudio.org/) is an integrated development environment (IDE) to support the development of R code. R Studio facilitates interaction with R.

10 More fancy GUIs R Studio R Studio ( is an integrated development environment (IDE) to support the development of R code. R Studio facilitates interaction with R. Console window for typing code Data window for reviewing data frame and other data structures Workspace for viewing all of the data loaded into R Plot area for showing visualisations Tabbed window controls to show other displays Some commands we already know (e. g. setwd() or rm(list=ls())) are integrated in Menues. In short, R Studio just organizes the different windows and workspaces and facilitates communication with R through short cuts and Menues. Finally, it has a convenient tool to Import Datasets: check out the Tab Import Dataset in the Window Workspace and History Exercise: Use Import Dataset to read the different files distributed last time. They should still be in the directory you created last time. Statistics for Biologists: Practicals HS / 22 More fancy GUIs R Studio Statistics for Biologists: Practicals HS / 22

11 More fancy GUIs R Studio Some other very usefull features are: Code completion: use tab key (tabulator) while within console or script also works in Script: pressing the tab key with the cursor on a function brings up a list of complete names of functions starting with say plot and a list of its arguments with a short explanation Spread-Sheet like display format clicking on a function in the Workspace window directly opens the corresponding code Integration of package management (demonstrate for Rcmdr) Statistics for Biologists: Practicals HS / 22 More fancy GUIs Rcmdr: R Commander, an R Package that needs to be downloaded and installed 4 Rcmdr is a graphical user interface for statistical analysis Rcmdr uses Menues and supports picking variable names from lists Rcmdr simplifies access to the most essential statistical analysis methods R runs in another window and can be used directly at any time Shows the code that it is running if you select Linear Regression from the Statistic Menue, Rcmdr tells you which R command it used. similarly, if you select histogram or boxplot from the Graphics Menue, Rcmdr tells you which R command it used. The R commands can then be copy pasted into a script and modified. Rcmdr may be helpful for beginners and for teaching. It s rareley used by more experienced users of R. 4 I will use this opportunity to demonstrate how to download and install R Packages Statistics for Biologists: Practicals HS / 22

Computer lab 2 Course: Introduction to R for Biologists

Computer lab 2 Course: Introduction to R for Biologists April 23, 2012 1 Scripting As you have seen, you often want to run a sequence of commands several times, perhaps with small changes. An efficient