Outline day 4 May 30th

Transcription

1 Graphing in R: basic graphing ggplot2 package Outline day 4 May 30th 05/

2 Graphing in R: basic graphing 05/

3 basic graphing Producing graphs R-base package graphics offers funcaons for producing many plots, for example: scafer plots plot() histograma hist() boxplots boxplot() bar plots barplot() pie charts pie() 05/

4 basic graphing ScaFer plots A sca&er plot is a type of plot or mathema2cal diagram using Cartesian coordinates to display values for typically two variables for a set of data. [Wikipedia] 05/

5 basic graphing Basic scafer plot x <- 1:10 y <- x^2 plot(x, y) 05/

6 basic graphing ScaFer plot plot(x, y, col="red", pch=2, type="b", main="a pre?y sca?er plot") 05/

7 basic graphing ScaFer plot plot(x, y, col=1:10, pch=1:10, cex=1:10, type="b", main="a pre?y sca?er plot") 05/

8 basic graphing Barplots A bar chart or bar graph is a chart that presents grouped data with rectangular bars with lengths propor2onal to the values that they represent. [Wikipedia] 05/

9 basic graphing Barplot x <- rep(c("geek", "nerd", "dork"), c(10,5,3)) barplot(table(x)) 05/

10 basic graphing Pie chart A pie chart is a circular sta2s2cal graphic which is divided into slices to illustrate numerical propor2on. [Wikipedia] 05/

11 basic graphing Pie chart x <- rep(c("geek", "nerd", "dork"), c(10,5,3)) pie(table(x)) 05/

12 basic graphing Boxplots In descrip2ve sta2s2cs, a boxplot is a convenient way of graphically depic2ng groups of numerical data through their quar2les. [Wikipedia] 05/

13 basic graphing Boxplots x <- matrix(rnorm(1000), ncol=2) 05/

14 basic graphing Histograms A histogram is a plot that lets you discover, and show, the underlying frequency distribu2on of a set of con2nuous data. [Wikipedia] 05/

15 basic graphing x <- rnorm(200) hist(x) Histogram 05/

16 basic graphing ExporAng graphs Graphs can be saved into many formats, including: pdf, jpeg, bmp, Dff. Open the file to save your plot in: Produce a graph: And close it: pdf("my_graph.pdf") plot(1:10) dev.off() 05/

17 basic graphing From R Studio: ExporAng graphs 05/

18 Exercise 9: Basic plots 05/

19 Graphing in R: IntroducDon to ggplot2 package 05/

20 graphing in R: ggplot2 ggplot2 Graphing package inspired by the Grammar of Graphics seminal work of Leland Wilkinson. A tool that enables to concisely describe the components of a graphic. 05/

21 graphing in R: ggplot2 ggplot2 Flexible Customizable PreFy Well documented 05/

22 graphing in R: ggplot2 ggplot2 Base layer to plot two variables: ggplot(dataframe, aes(x, y)) Add layer specifying what kind of plot you want. Example of a scafer plot: ggplot(dataframe, aes(x, y)) + geom_point() 05/

23 graphing in R: ggplot2 ScaFer plots df1 <- data.frame(sample1=rnorm(200), sample2=rnorm(200)) ggplot(df1, aes(x=sample1, y=sample2)) + geom_point() 05/

24 graphing in R: ggplot2 ScaFer plots Store the graph in an object: p <- ggplot(df1, aes(x=sample1, y=sample2)) + geom_point() add layers to p: Atle with ggdtle("my Atle") veracal line with geom_vline(xintercept=2) etc. p + ggatle( ) 05/

25 graphing in R: ggplot2 ScaFer plots p <- ggplot(df1, aes(x=sample1, y=sample2)) + geom_point() add Atle with ggdtle p2 <- p + ggdtle("atle of the plot") draw a veracal with geom_vline p3 <- p2 + geom_vline(xintercept=0) 05/

26 graphing in R: ggplot2 ScaFer plots Color according to another column: df2 <- data.frame(df1, grouping=rep(c("yes", "no"), c(80, 120))) p <- ggplot(df2, aes(sample1, sample2, color=grouping)) + geom_point() 05/

27 graphing in R: ggplot2 ScaFer plots p <- ggplot(df2, aes(sample1, sample2, color=grouping)) + geom_point() 05/

28 graphing in R: ggplot2 Boxplots ggplot(df2, aes(x=1, y=sample1)) + geom_boxplot() 05/

29 graphing in R: ggplot2 Boxplots ggplot(df2, aes(x=grouping, y=sample1)) + geom_boxplot() 05/

30 graphing in R: ggplot2 Boxplots Plofng both sample1 and sample2? Need to convert the data frame into a long format! 05/

31 graphing in R: ggplot2 wide Wide vs long formats genename sample1 sample2 grouping gene1 6 3 UP gene DOWN gene NONE long gene UP genename grouping variable value library(reshape2)?melt gene1 UP sample1 6 gene2 DOWN sample1 2.7 gene3 NONE sample1 3.2 gene4 UP sample1 4.7 gene1 UP sample2 3 gene2 DOWN sample2 5.1 gene3 NONE sample2 3.3 gene4 UP sample /

32 graphing in R: ggplot2 Boxplots Plofng both sample1 and sample2? Convert to long format df_long <- melt(df2) 05/

33 graphing in R: ggplot2 Boxplots ggplot(df_long, aes(x=variable, y=value)) + geom_boxplot() 05/

34 graphing in R: ggplot2 Boxplots ggplot(df_long, aes(x=variable, y=value, color=grouping)) + geom_boxplot() 05/

35 graphing in R: ggplot2 Barplots p <- ggplot(df2, aes(x=grouping)) + geom_bar() 05/

36 graphing in R: ggplot2 Barplots p <- ggplot(df2, aes(x=grouping)) + geom_bar() Change x axis label with scale_x_discrete: p2 <- p + scale_x_discrete(name= How many yes and no") Swapping x and y axis with coord_flip(): p3 <- p2 + coord_flip() 05/

37 graphing in R: ggplot2 Barplots 05/

38 graphing in R: ggplot2 Histograms ggplot(df_long, aes(x=value)) + geom_histogram() 05/

39 graphing in R: ggplot2 Histograms ggplot(df_long, aes(x=value, fill=variable)) + geom_histogram() default: stacked! 05/

40 graphing in R: ggplot2 Histograms ggplot(df_long, aes(x=value, fill=variable)) + geom_histogram(posiaon='idenaty') 05/

41 graphing in R: ggplot2 Histograms ggplot(df_long, aes(x=value, fill=variable)) + geom_histogram(posiaon='dodge') 05/

42 Exercise 10: IntroducDon to ggplot2 05/

43 Wrap up: what did we learn in those 12 hours? RStudio Data structures Vector Matrix Data frame Lists Input/Output Packages Plofng basic plofng ggplot2 05/

44 What s next? Stats next week! Loops FuncAons R Mark Down... Anything you want to learn? à Contact sarah.bonnin@crg.eu and/or damjana.kastelic@crg.eu 05/

45 R Studio Cheat sheets hfps:// cheatsheets/ hfps:// 2016/11/ggplot2-cheatsheet-2.1.pdf 05/

46 Online courses EDX/Coursera courses: hfps:// hfps:// hfps:// hfps:// hfps:// 05/

47 Forums R mailing lists: hfps:// Bioconductor forum: hfps://support.bioconductor.org/ 05/

48 Thanks! Sarah Bonnin CRG BioinformaAcs unit Estefania Mancini Lab Juan Valcárcel 05/

49 More useful basic commands 05/

50 More commands Some common arithmeac funcaons natural logarithm exponenaal funcaon e^x sine cosine tangent absolute value square root log(x) exp(x) sin(x) cos(x) tan(x) abs(x) sqrt(x) 05/

51 More commands Objects stored in the global environment LisAng: ls() or objects() Removing one object from environment: rm(x) Removing several objects: rm(x, y) Removing all object from environment: rm(list=ls()) 05/

52 More commands Saving objects or session Save objects x and y into "myobjects.rdata" file save(x, y, file="myobjects.rdata") Load objects x and y into current directory: load("myobjects.rdata") Save the current workspace (all objects): save.image(file=".rdata") 05/

53 More commands Command history Last 25 commands: history() All previous commands history(max.show=inf) Save command history: savehistory() Load command history: loadhistory() 05/

54 More commands InformaAon about the current session sessioninfo() R version Pla\orm and OS version Packages a?ached 05/

55 WriDng funcdons in R 05/

56 Func=ons User-wriFen funcaons FuncAons are pieces of code wrifen to carry out specified tasks and be able to repeat them easily. R allows you to create your own funcaons. 05/

57 Func=ons FuncAons structure FuncDon s name CreaDng the funcdon myfuncdon s list of arguments myfuncdon <- funcdon(arg1, arg2,... ){ } commands return(something) what myfuncdon does Value / object myfuncdon returns 05/

58 Func=ons Objects in funcaons myfuncdon <- funcdon(arg1){ a <- arg1 return(a+1) } > myfuncaon(10) [1] 11 > a Error: object 'a' not found > a <- 12 > myfuncaon(10) [1] 11 > a [1] 12 05/