Introduction to R - Weeblydiversityinlife.weebly.com/uploads/1/2/8/6/12864099/r... · 2019-08-21 · Introduction to R R-peer-group QUB February 5, 2013 R-peer-group (QUB) Session

Introduction to R

R-peer-group

QUB

February 5, 2013

R-peer-group (QUB) Session 1 February 5, 2013 1 / 46

Introductions

Some things to startTo download this presentation follow this link:http://tinyurl.com/aone2s6

Join the biology-r-users list by emailling Stephen Fowler<[email protected]>

This mailing list can be used for:

-> Asking for help with R

-> Giving help with R

-> Telling people about something cool you’ve learned in R

-> Sharing R resources (e.g. links, pdfs)-> Discussing these sessions

A handy list of useful resources can be downloaded from this link:http://tinyurl.com/awg76t7


http://tinyurl.com/aone2s6

http://tinyurl.com/awg76t7

Introductions

Who are the R-peer-group?


Helene Bovy

What do I use R for?All my analyses!

Research area?Invasion ecology, behavioural ecology. In the past, populationdynamics and image analysis.

Favorite feature?It makes you think about what you’re doing (and understand!)


Helene Bovy

What has R ever done for us?


Mark Emmerson

Mark’s QUB Profile


http://www.qub.ac.uk/schools/SchoolofBiologicalSciences/People/ProfessorMCEmmerson/

Kevin Keenan

What do I use R for?Everything! (Genetics data analysis, folder organisation, file re-namer,plotting, programming, LATEX(Sweave), software development,bioinformatics, data management, data manipulation, GIS)

Research area?Evolutionary and population genetics.

Favorite feature?It’s free!


Kevin Keenan



Ruth Kelly

What do I use R for?Statistical analyses (e.g. GLMMs, GAMs, multivariate analyses andbasic simulation models). I still use ArcView GIS for some spatialwork and MaxEnt for distribution modelling.

Research area?Spatial ecology and Botany

Favorite feature?Repeatability - stored code allows me to exactly replicate analyses andto remember exactly what I did!


Ruth Kelly

What has R ever done for us?Made analyses much faster (especially model selection and mapcalculations)


Jack Lennon

What do I use R for?

-> Spatial analysis and modelling-> Figures for publication-> To organise data and then call other more specialised packages (e.g.

WinBUGS, C++ code), for analysis

Research area?Spatial ecology and macroecology


-> Brought more researchers into the modelling/analysis fold who hithertocouldn’t/wouldn’t get involved in FORTRAN or C programming.

-> Hugely accelerated the development and exchange of novel ways ofanalysis and displaying scientific data

Favorite feature?Data manipulation (e.g. aggregate() function) and plotting features.


Jack Lennon



Rob Mrowicki

What do I use R for?Ecological data analysis, making plots/figures

Research area? Marine biodiversity and ecosystem functioning

Favorite feature? Help is always available!


Rob Mrowicki

What has R ever done for us?All of my analysis and plotting (so far)... as well as making me feelclever.


Mark Ravinet

What do I use R for?Basic data manipulation and analysis mixed models, Bayesianmodelling of stable isotope data, phylogenetic analysis and plottingpretty figures.

Research area?Evolutionary biology and ecological speciation.

Favorite feature?The ability to look at the script for a function and modify it to makeit do what I’d like it to!


Mark Ravinet



Course content

The course is intended for all post-grad/post-doc/academics whowant to learn R

It will cover a wide range of topics

-> you might want to attend one, a few, or all sessions

Table 1: A broad outline of themes within the course

Basic Intermediate Advanced

What is R? GLM GISArithmetic GAM sPCA

T-test Indexing nested objects Reproducible researchChi-square Code automation Writing functions

Read/Write data Data manipulation Analysis optimisationsIndexing Plotting HPC


Course format

A focus on discussion (Q & A)

Informal

Subject themes (e.g. Multivariate statistics, Visualising data)

Emphasis on practical labs and demonstrations

2 hour sessions held every Tuesday (05/02/13 - ??/??/13)

Optional homework for some sessions

Course content is open to change for popular topic suggestions


What is R?

R is a language and environment for statistical computing andgraphics

Language

-> Highly customisable, flexible and powerful-> R was originally developed at the university of Auckland, NZ

Environment

-> Supports the integration of many processes into one singlework-flow/pipeline

-> Highly extensible


What is R?

It is used widely in academic and commercial sectors

It is one of the most popular analytical softwares used amongprofessional data analysts


pros and cons

pros

-> Fully functional statistical programming environment-> Open source-> Cross platform can be used on all popular operating systems-> Excellent graphics capabilities-> Thousands of (free) extension packages.-> Large online community of users and developers-> Analysis frameworks can be saved in reproducible formats.-> High level programming language

cons

-> Steep learning curve (We’ll help here)-> Minimal GUI capabilities-> Analysing large data sets can be troublesome (??bigmemory)-> Scripts cannot be compiled into stand alone .exe programs-> Interpreted language, slow.-> Thousands of (free) extension packages.


What R can do for you

Basic calculator

> 10 * 10

[1] 100

Advanced calculator

FormulaIn(Q; J = j) = −pj logepj +

∑Ki=1

pijK logepij

Code> In <- (-(p[j])*log(p[j])) + sum((p[i, j]/k)*log(p[i, j]))



Writing Programs> #define a program (function)

> letterCount <- function(infile){

+ if(!is.character(infile)){

+ infile <- as.character(infile)

+ }

+ phrase <- scan(infile, what = "", sep = "\n", quiet = TRUE)

+ letters1<-unlist(strsplit(phrase,""))

+ alpha<-c(letters[1:26],LETTERS[1:26])

+ sorter<-function(x){

+ if(is.element(x,alpha)==TRUE){

+ return (x)

+ } else {

+ return (NA)

+ }

+ }

+ lettersCount<-lapply(letters1,sorter)

+ uplowFix <- lapply(lettersCount, function(x){

+ if(is.element(x, LETTERS)){

+ return(x <- letters[which(LETTERS == x)])

+ } else {

+ return(x)

+ }

+ })

+ lettersCount<-na.omit(unlist(uplowFix))

+ x<-table(lettersCount)

+ plot(x, ylab = "Number Used", col = rainbow(26), las = 1)

+ return(x)

+ }



Running programs

> # run the program to see the results

> x <- letterCount("text.txt")

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lettersCount

Num

ber

Use

d

a c e g i m o r t v x



Designing web applications

Stocks app

Global Biodiversity Facility

Price trajectories

Gene Networks

Finance Showreel


http://glimmer.rstudio.com/winston/stocks/

http://glimmer.rstudio.com/ropensci/rgbif2/

http://glimmer.rstudio.com/timelyportfolio/d3-shiny-cpi/

http://glimmer.rstudio.com/qbrc/grn/

http://glimmer.rstudio.com/timelyportfolio/shiny-d3-showreel/


Data analysis

-> General statistical tests(t.test, anova, glm, chisq.test, lm)

-> Specialised statistical packages(abc, BSgenome, cluster, igraph, shapefiles)

Data Visualisation

-> Basic plots

−3 −2 −1 0 1 2 3

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x

y



Data visualisation-> Animated plots-> Advanced plots

t1t2t3t4t5t6t7t8t9t10t11t12t13t14t15t16t17t18t19t20t21t22t23t24t25t26t27t28t29t30t31t32t33t34t35t36t37t38t39t40t41t42t43t44t45t46t47t48t49t50t51t52t53t54t55t56t57t58t59t60t61t62t63t64t65t66t67t68t69t70t71t72t73t74t75t76t77t78t79t80t81t82t83t84t85t86t87t88t89t90t91



Generate .kml files for use in GoogleEarth (R2G2).



Having fun-> Read XKCD comic strips

> library(RXKCD)

> getXKCD(searchXKCD(which = "programming")[1,"num"])



Having fun!-> Browsing twitter

library(twitteR)

rProg <- searchTwitter('#r programming', n = 500)

pythonProg <- searchTwitter('#python programming', n = 500)

cProg <- searchTwitter('#c programming', n = 500)

#R programming #python programming #c programming

Programming language mentions in twitter

twitt

er m

entio

ns

010

020

030

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0


Practical sessions

Exploring RStudioFolder management, R projects, the R console,

help, R scripts and more


Practical sessions

Objects in R


Vectors

Vectors are the most simple objects in R

-> Can contain one or many elements

They can contain character, integer, numeric, complex, logical orraw value classes (atomic)

All elements in a vector must be the same class (e.g. all numeric)

Vectors can be manually passed to the R console or assigned tovariable names

-> Manual

> c(1,2,3,4,5) # Use c to combine elements

[1] 1 2 3 4 5

-> Assignment

> x <- c(1,2,3,4,5) # Assign the vector to the variable x


Vectors

If we have two numeric/complex/integer/logical/raw vectors we canadd them together

> x <- c(1,2,3,4,5) # Create a vector variable x

> y <- c(5,4,3,2,1) # Create a vector variable y

> x + y # sum of x and y

[1] 6 6 6 6 6

Or divide them> x / y # x divided by y

[1] 0.2 0.5 1.0 2.0 5.0

Or multiply them> x * y # x multiplied by y

[1] 5 8 9 8 5

> # Assignment

> z <- x * y # assign the value x * y to the

> # variable z


Vectors

What if you wanted to find out what the value of a particular elementof a variable is?

-> Index mapping> x # print x

[1] 1 2 3 4 5

> x[3] # 3rd element of x

[1] 3

> x[2:4] # elements 2 to 4 of x

[1] 2 3 4

> x[-4] # all elements of x except the 4th

[1] 1 2 3 5

> x[3] * y[3] # Multiply the 3rd elements of x and y

[1] 9


Vectors

Using index mapping we can change the value of individual elements> x[1] <- 50 # Make the 1st element of x = 50

> x # print x

[1] 50 2 3 4 5

There are many ways to manually create vectors in R

> # Using the colon, ':'> x <- 1:10

> # Using the combine function 'c'> x <- c(1,2,3,4,5,6,7,8,9,10)

> # Using the function 'seq'> x <- seq(from = 1, to = 10, by = 1)

> # Create a string vector

> y <- c("apples", "oranges")


Do it yourself

Try to do the following few tasks. Instructors will walk around to helpyou.

1 Create a character vector and assign it to the variable myName. Thevector should contain two character elements corresponding to yourfirst and second names. Print myName to the console.

2 Create a numeric vector x, with elements from 5 to 100 increasing insteps of 5.

Hint-Remember there are more than one way to create a vector in R.Try typing each of the following (exactly as shown here), into the Rconsole to see which way you should use.

-> ?colon

-> ?c

-> ?seq

3 Assign the variable surName with value equal to the second element ofyour variable myName without re-typing your surname into the console.


Do it yourself

Questions continued.

4 Create a vector y. Its elements should equal to the square of thecorresponding element in x. For example, if the last element in x = 10then the last element in y should be 100 or 102 = 100

Hint-You do not need to calculate each element separately. R has afeature called vectorisation meaning it can apply an operation to anentire vector rather than having to do it to one value at a time. Theoperator of interest in this case is ^.

5 Assign the results of the following calculations to variable names ofyour choice.

-> The product of the vectors x and y

-> The result of x times itself-> The result of taking the square root of the vector y

Hint-Taking the square root of a value is the same as raising it to thepower of 0.5


What else can you do with vectors?

We can also use R to answer logical questions about objects.

-> Imagine we want to ask R if first element of two vectors are equal.We could do this by typing the following:

> x == y

[1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE

[8] FALSE FALSE FALSE FALSE FALSE FALSE FALSE

[15] FALSE FALSE FALSE FALSE FALSE FALSE

-> As expected, none of the values in x are equal to the correspondingvalues in y.

This type of query is important when checking the output of analyses.Very useful for debugging scripts before applying them to your realdata.

-> How do you think you could ask R if two elements from a vector werethe same?


What about functions?

Functions are small programs that make R so useful.

They are usually made up of very simple commands pieced togetherto carry out a complex process.

Functions accept arguments. These can be data or parameters.

We have already seen the function seq which we know accepts threearguments in its most common use.

> seq(from = 1, to = 10, by = 1)

Most functions work in a very similar way to this function. You simplyhave to provide the correct arguments for them to work.


Using functions

We can find out about the arguments required by a functions by usingthe built in R help system.

At the most general level, we saw earlier that by typinghelp.start() we could launch a help manual for R. However, thereare more specific help functions available.

help()

help.search()

?

??

Usually the ? help functions is sufficient for finding out aboutfunctions. How does it work?


Using functions

Type the following commands into the R console.

?sum

?prod

?seq

?mean

?sqrt

Using the functions prod() and sqrt() repeat the following threetasks(N.B. read the help documentation to find out how to use these functions):

-> The product of the vectors x and y

-> The result of x times itself-> The result of taking the square root of the vector y-> Ask R if x is equal to the square-root of y


Visualising variables

Often it is necessary to visualise variables to understand the types ofstatistical test you might need to do

In simple cases we can visualise variables using the plot function.> x <- rnorm(n = 1000, mean = 10, sd = 5)

> y <- x^2

> plot(y ~ x)

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Some final challenges

An American colleague has collected samples of American eels,Anguilla rostrata for a research paper you are working on. They havesent you a vector of adult fish lengths as well as the mean andstandard deviation of the data as follows:

Lengths

[1] 46.58 44.25 41.27 44.70 46.94 4.23 46.25

[8] 44.03 46.04 46.55

Mean length

[1] 45.105

Standard deviation of the mean

[1] 1.7326



Tasks

a) Check to make sure that the mean and standard deviation given to youcorresponds to the mean and standard deviation of the data you’verecorded.

b) If there is a problem what do you think it is considering the fact thatyour colleague has told you that all fish were longer than 40 inches?

-> Which value in the data is incorrect?-> What should the correct value be?-> Replace the incorrect value with the right one

c) Using logical tests, check that the mean and sd sent to you by yourcolleague are the correct ones?



The values your colleague has sent you are well below the standardlengths reported for all populations of eels studied to date. Youremember that the data have been recorded in the imperial units,inches rather than the expected metric units, cm. Using the functionsand techniques demonstrated today,

d) Convert your vector of lengths from inches to cm, saving the results ina new vector. [1 inch = 2.54 cm]

Hint-There may be functions that can do this for you!

e) Calculate the new mean and standard deviation of the converted data.

f) Calculate the variance of both data sets. [sd =√Var(x)].


Documents

Introduction to R - Weeblydiversityinlife.weebly.com/uploads/1/2/8/6/12864099/r... · 2019-08-21 · Introduction to R R-peer-group QUB February 5, 2013 R-peer-group (QUB) Session