Intro to using R for Bioinformatics: Part 1 : The Basics

Angel Pizarroangel@upenn.edu

Injecting a bit of reality

Taking it a bit further…

Waxing floors is not fun, and may not seem relevant, but have some faith Daniel-san

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.

What is ?R is a language and environment for statistical computing and graphics.

– http://www.r-project.org

You can do stuff like this

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

Help is plentiful

Help in three ways

Too much! Get me out!

More Helphelp.start()

– Start an HTML help session

help(mean)– Looks up the mean()

function's help page– ?mean

help.search(mean) – Displays all help pages that

contain text “mean”– ??mean

Whet your appetite…

The Basics

• Please enter each of the following lines into your R session:

Basic Algebra

You will also see this form:

Variables

• “x” and “y” are variables. • They are pointers to some value• They can also be pointers to some function

Vectors

Enter this in your session: Results

Small tangent: What is “c (1,2,3)”?

• Use the help()

Accessing Vector MembersIn 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

Small Tangent 2: Creating Sequences

• Create regular sequences using a colon

• Colon has high operator precedence

• Also see the seq() function

Vectors

• Are a list of items of the same data type

Short for “double precision floating point number”

Doing Stuff with Vectors

• Math operations occur on each element in sequence

• Returns a vector of the same size

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

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

Example

An INDEX ARRAY

List

• An ordered collection of named components

List Access

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

Functions

• We’ve already used them• Functions take in arguments and perform

some action using those arguments. • Actions do not affect the input arguments

Example

Write to CSV file

Extra column of the row indices

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

Start from your save point