How to install R and a Brief Introduction to R — Bioinformatics 0.1 documentation (2024)

Introduction to R¶

This little booklet has some information on how to use R for bioinformatics.

R (www.r-project.org) is a commonly usedfree Statistics software. R allows you to carry out statisticalanalyses in an interactive mode, as well as allowing simple programming.

Installing R¶

To use R, you first need to install the R program on your computer.

Installing R packages¶

R comes with some standard packages that are installed when you install R. However, in thisbooklet I will also tell you how to use some additional R packages that are useful, for example,the “rmeta” package. These additional packages do not come with the standard installation of R,so you need to install them yourself.

> library("rmeta")

> source("http://bioconductor.org/biocl*te.R")> biocl*te()

> source("http://bioconductor.org/biocl*te.R")> biocl*te("yeastExpData")

> library("yeastExpData")

Running R¶

To use R, you first need to start the R program on your computer.You should have already installed R on your computer (see above).

To start R, you can either follow step 1 or 2:1. Check if there is an “R” icon on the desktop of the computer that you are using.

If so, double-click on the “R” icon to start R. If you cannot find an “R” icon, try step 2 instead.

2. Click on the “Start” button at the bottom left of your computer screen, and then choose “All programs”, and start R by selecting “R” (or R X.X.X, where X.X.X gives the version of R, eg. R 2.10.0) from the menu of programs.

This should bring up a new window, which is the R console.

A brief introduction to R¶

You will type R commands into the R console in order to carry outanalyses in R. In the R console you will see:

>

This is the R prompt. We type the commands needed for a particulartask after this prompt. The command is carried out after you hitthe Return key.

Once you have started R, you can start typing in commands, and theresults will be calculated immediately, for example:

> 2*3[1] 6> 10-3[1] 7

All variables (scalars, vectors, matrices, etc.) created by R arecalled objects. In R, we assign values to variables using anarrow. For example, we can assign the value 2*3 to the variablex using the command:

> x <- 2*3

To view the contents of any R object, just type its name, and thecontents of that R object will be displayed:

> x[1] 6

There are several possible different types of objects in R,including scalars, vectors, matrices, arrays, data frames, tables,and lists. The scalar variable x above is one example of an Robject. While a scalar variable such as x has just one element, avector consists of several elements. The elements in a vector areall of the same type (eg. numeric or characters), while lists mayinclude elements such as characters as well as numeric quantities.

To create a vector, we can use the c() (combine) function. Forexample, to create a vector called myvector that has elementswith values 8, 6, 9, 10, and 5, we type:

> myvector <- c(8, 6, 9, 10, 5)

To see the contents of the variable myvector, we can just typeits name:

> myvector[1] 8 6 9 10 5

The [1] is the index of the first element in the vector. We canextract any element of the vector by typing the vector name withthe index of that element given in square brackets. For example, toget the value of the 4th element in the vector myvector, wetype:

> myvector[4][1] 10

In contrast to a vector, a list can contain elements of differenttypes, for example, both numeric and character elements. A list canalso include other variables such as a vector. The list() functionis used to create a list. For example, we could create a listmylist by typing:

> mylist <- list(name="Fred", wife="Mary", myvector)

We can then print out the contents of the list mylist by typingits name:

> mylist$name[1] "Fred"$wife[1] "Mary"[[3]][1] 8 6 9 10 5

The elements in a list are numbered, and can be referred to usingindices. We can extract an element of a list by typing the listname with the index of the element given in double square brackets(in contrast to a vector, where we only use single squarebrackets). Thus, we can extract the second and third elements frommylist by typing:

> mylist[[2]][1] "Mary"> mylist[[3]][1] 8 6 9 10 5

Elements of lists may also be named, and in this case the elementsmay be referred to by giving the list name, followed by “$”,followed by the element name. For example, mylist$name is thesame as mylist[[1]] and mylist$wife is the same asmylist[[2]]:

> mylist$wife[1] "Mary"

We can find out the names of the named elements in a list by usingthe attributes() function, for example:

> attributes(mylist)$names[1] "name" "wife" ""

When you use the attributes() function to find the named elementsof a list variable, the named elements are always listed under aheading “$names”. Therefore, we see that the named elements of thelist variable mylist are called “name” and “wife”, and we canretrieve their values by typing mylist$name and mylist$wife,respectively.

Another type of object that you will encounter in R is a tablevariable. For example, if we made a vector variable mynamescontaining the names of children in a class, we can use the table()function to produce a table variable that contains the number ofchildren with each possible name:

> mynames <- c("Mary", "John", "Ann", "Sinead", "Joe", "Mary", "Jim", "John", "Simon")> table(mynames)mynames Ann Jim Joe John Mary Simon Sinead 1 1 1 2 2 1 1

We can store the table variable produced by the function table(),and call the stored table “mytable”, by typing:

> mytable <- table(mynames)

To access elements in a table variable, you need to use doublesquare brackets, just like accessing elements in a list. Forexample, to access the fourth element in the table mytable (thenumber of children called “John”), we type:

> mytable[[4]][1] 2

Alternatively, you can use the name of the fourth element inthe table (“John”) to find the value of that table element:

> mytable[["John"]][1] 2

Functions in R usually require arguments, which are inputvariables (ie. objects) that are passed to them, which they thencarry out some operation on. For example, the log10() function ispassed a number, and it then calculates the log to the base 10 ofthat number:

> log10(100)2

In R, you can get help about a particular function by using thehelp() function. For example, if you want help about the log10()function, you can type:

> help("log10")

When you use the help() function, a box or webpage will pop up withinformation about the function that you asked for help with.

If you are not sure of the name of a function, but think you knowpart of its name, you can search for the function name using thehelp.search() and RSiteSearch() functions. The help.search() functionsearches to see if you already have a function installed (from one ofthe R packages that you have installed) that may be related to sometopic you’re interested in. The RSiteSearch() function searches allR functions (including those in packages that you haven’t yet installed)for functions related to the topic you are interested in.

For example, if you want to know if thereis a function to calculate the standard deviation of a set ofnumbers, you can search for the names of all installed functions containingthe word “deviation” in their description by typing:

> help.search("deviation")Help files with alias or concept or title matching'deviation' using fuzzy matching:genefilter::rowSds Row variance and standard deviation of a numeric arraynlme::pooledSD Extract Pooled Standard Deviationstats::mad Median Absolute Deviationstats::sd Standard Deviationvsn::meanSdPlot Plot row standard deviations versus row

Among the functions that were found, is the function sd() in the“stats” package (an R package that comes with the standard Rinstallation), which is used for calculating the standard deviation.

In the example above, the help.search() function found a relevantfunction (sd() here). However, if you did not find what you were lookingfor with help.search(), you could then use the RSiteSearch() function tosee if a search of all functions described on the R website may findsomething relevant to the topic that you’re interested in:

> RSiteSearch("deviation")

The results of the RSiteSearch() function will be hits to descriptionsof R functions, as well as to R mailing list discussions of thosefunctions.

We can perform computations with R using objects such as scalarsand vectors. For example, to calculate the average of the values inthe vector myvector (ie. the average of 8, 6, 9, 10 and 5), wecan use the mean() function:

> mean(myvector)[1] 7.6

We have been using built-in R functions such as mean(),length(), print(), plot(), etc. We can also create our ownfunctions in R to do calculations that you want to carry out veryoften on different input data sets. For example, we can create afunction to calculate the value of 20 plus square of some inputnumber:

> myfunction <- function(x) { return(20 + (x*x)) }

This function will calculate the square of a number (x), and thenadd 20 to that value. The return() statement returns the calculatedvalue. Once you have typed in this function, the function is thenavailable for use. For example, we can use the function fordifferent input numbers (eg. 10, 25):

> myfunction(10)[1] 120> myfunction(25)[1] 645

To quit R, type:

> q()

Links and Further Reading¶

Some links are included here for further reading.

For a more in-depth introduction to R, a good online tutorial isavailable on the “Kickstarting R” website,cran.r-project.org/doc/contrib/Lemon-kickstart.

There is another nice (slightly more in-depth) tutorial to Ravailable on the “Introduction to R” website,cran.r-project.org/doc/manuals/R-intro.html.

Acknowledgements¶

For very helpful comments and suggestions for improvements on the installation instructions, thank you very much to Friedrich Leisch and Phil Spector.

License¶

The content in this book is licensed under a Creative Commons Attribution 3.0 License.