Using ggplot2

In [1]:

suppressPackageStartupMessages(library(tidyverse))

Warning message:
“Installed Rcpp (0.12.12) different from Rcpp used to build dplyr (0.12.11).
Please reinstall dplyr to avoid random crashes or undefined behavior.”Warning message:
“package ‘dplyr’ was built under R version 3.4.1”

In [2]:

head(iris)
Sepal.LengthSepal.WidthPetal.LengthPetal.WidthSpecies
5.1 3.5 1.4 0.2 setosa
4.9 3.0 1.4 0.2 setosa
4.7 3.2 1.3 0.2 setosa
4.6 3.1 1.5 0.2 setosa
5.0 3.6 1.4 0.2 setosa
5.4 3.9 1.7 0.4 setosa
 
In [3]:

options(repr.plot.width=4, repr.plot.height=3)

Map data attributes to aesthetics

In [4]:

g <- ggplot(iris, aes(x=Sepal.Length, y=Sepal.Width, color=Species))
g
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_5_1.png

Use different geometries for the same mapping

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g + geom_point()
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_7_1.png 
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g + geom_density2d()
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_8_1.png 
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g + geom_smooth()

`geom_smooth()` using method = 'loess'
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_9_2.png

Combine geometries

In [8]:

g + geom_point() + geom_smooth()

`geom_smooth()` using method = 'loess'
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_11_2.png

Changing labels

In [9]:

g + geom_point() + geom_smooth() +
labs(x="Sepal Length", y="Sepa; Width", title="Iris", subtitle="Plotted with ggplot")

`geom_smooth()` using method = 'loess'
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_13_2.png

Changing scales

In [10]:

g +
geom_jitter(width = 0.2) +
scale_y_log10()
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_15_1.png

Group plots using facets

In [11]:

g + geom_point() + geom_smooth() +
facet_wrap(~ Species)

`geom_smooth()` using method = 'loess'
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_17_2.png 
In [12]:

g + geom_point() + geom_smooth() +
facet_wrap(~ Species, ncol = 1)

`geom_smooth()` using method = 'loess'
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_18_2.png

Turning guides on and off

In [13]:

g + geom_point() + geom_smooth() +
facet_wrap(~ Species) +
guides(color=FALSE)

`geom_smooth()` using method = 'loess'
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_20_2.png

Reshaping data.frames with gather and plotting

In [14]:

iris %>% gather(measure, value, -Species) %>% head
Speciesmeasurevalue
setosa Sepal.Length5.1
setosa Sepal.Length4.9
setosa Sepal.Length4.7
setosa Sepal.Length4.6
setosa Sepal.Length5.0
setosa Sepal.Length5.4 
In [15]:

options(repr.plot.width=6, repr.plot.height=4)

In [16]:

g2 <- ggplot(iris %>% gather(measure, value, -Species),
            aes(x=Species, y=value, fill=Species, color=Species))

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g2 + facet_wrap(~ measure) + geom_boxplot()
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_25_1.png 
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g2 + facet_wrap(~ measure) + geom_jitter()
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../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_26_1.png 
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g2 + facet_wrap(~ measure) + geom_bar(stat="identity")
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_27_1.png

Allowing different scales for each plot

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g2 + facet_wrap(~ measure, scales="free") + geom_boxplot()
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_29_1.png

Change coordinates

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g2 +
geom_boxplot() +
coord_flip()
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_31_1.png 
In [22]:

options(repr.plot.width=6, repr.plot.height=6)

In [23]:

polar <- g2 +
facet_wrap(~ measure) +
geom_jitter(width = 0.2, size=1) +
coord_polar() +
guides(color=FALSE, fill=FALSE) +
labs(x="", y="")

In [24]:

polar
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_34_1.png

Transparency

In [25]:

ggplot(iris, aes(x=Sepal.Length, fill=Species)) +
geom_density(alpha=0.5)
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_36_1.png

Themes

In [26]:

ggplot(iris, aes(x=Sepal.Length, fill=Species)) +
geom_density(alpha=0.5) +
theme_bw()
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_38_1.png 
In [28]:

ggplot(iris, aes(x=Sepal.Length, fill=Species)) +
geom_density(alpha=0.5) +
theme_classic()
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_39_1.png 
In [247]:

ggplot(iris, aes(x=Sepal.Length, fill=Species)) +
geom_density(alpha=0.5) +
theme_dark() +
theme(axis.text.x = element_text(colour = 'red', size=20),
      axis.text.y = element_text(color = 'blue', size=20))
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_40_1.png

Using color scales

In [62]:

options(repr.plot.width=4, repr.plot.height=3)

Discrete colors or fills

In [63]:

g3 <- ggplot(iris %>% gather(measure, value, -Species),
            aes(x=Species, y=value, fill=Species)) +
     geom_bar(stat="identity")

In [64]:

g3
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_45_1.png 
In [69]:

g3 + scale_fill_brewer(type='seq')
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_46_1.png 
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g3 + scale_fill_brewer(type='div')
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_47_1.png 
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g3 + scale_fill_brewer(type='qual')
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_48_1.png 
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g3 + scale_fill_brewer(type='seq', palette = 'Reds')
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_49_1.png 
In [76]:

g3 + scale_fill_brewer(type='seq', palette = 'Reds', direction = -1)
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_50_1.png

Continuous colors or fills

In [110]:

suppressPackageStartupMessages(library(genefilter))

In [116]:

n <- 20
m <- 50000
EXPRS <- matrix(rnorm(m * 2 * n), m, 2*n)
rownames(EXPRS) <- paste('g', 1:m, sep='')
colnames(EXPRS) <- paste('pt', 1:(2*n), sep='')
grp <- as.factor(rep(c("Control", "Treated"), each=n))

In [117]:

p.values <- rowttests(EXPRS, grp)$p.value
ii <- order(p.values)
TOPEXPRS <- EXPRS[ii[1:100], ]

In [119]:

M <- data.frame(t(TOPEXPRS)) %>% rownames_to_column("pid") %>% gather(gene, expression, -pid)

In [120]:

head(M)
pidgeneexpression
pt1 g156 -0.4724457
pt2 g156 0.3118261
pt3 g156 -0.4587830
pt4 g156 -1.1015636
pt5 g156 -0.3718592
pt6 g156 -1.0262855
 
In [165]:

options(repr.plot.width=6, repr.plot.height=4)

In [176]:

g4 <- ggplot(M, aes(gene, pid, fill=expression)) +
      geom_tile(colour='white') +
      theme(axis.text.x = element_blank(),
            axis.text.y = element_blank(),
            axis.ticks.x = element_blank(),
            axis.ticks.y = element_blank())

In [177]:

g4
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_59_1.png 
In [178]:

g4 + scale_fill_gradient(low = "white", high="red")
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_60_1.png 
In [188]:

g4 + scale_fill_gradient2(low = "darkgreen", high="darkblue")
Data type cannot be displayed:
../../_images/Computation_Wk4_Day1_AM_Using_ggplot2_61_1.png

Saving plots

In [197]:

ggsave('polar.png', polar)

Saving 7 x 7 in image

Check saved plot

Exercise

Hint: If nothing is plotted, wrap the entire R expression in a print() statement to see the error message.

In [199]:

head(mtcars)
mpgcyldisphpdratwtqsecvsamgearcarb
Mazda RX421.0 6 160 110 3.90 2.62016.460 1 4 4
Mazda RX4 Wag21.0 6 160 110 3.90 2.87517.020 1 4 4
Datsun 71022.8 4 108 93 3.85 2.32018.611 1 4 1
Hornet 4 Drive21.4 6 258 110 3.08 3.21519.441 0 3 1
Hornet Sportabout18.7 8 360 175 3.15 3.44017.020 0 3 2
Valiant18.1 6 225 105 2.76 3.46020.221 0 3 1

1. Make a scatter plot with y=mpg and x=wt

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2. Add a linear regression curve.

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3. Add a title ‘Fuel efficiency decreases with weight’, and rename the x and y axis to ‘Weight’ and ‘Miles per gallon’.

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4. Change the color of the scatter points to salmon.

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5. Change the color of the scatter points to represent the horsepower hp.

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6. Use color brewer to set the scale in Q4 with the Oranges seqeuntial palette for the cyl variable.

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7. Make a density plot of mpg and fill by the factor cyl, and set the transparecny to 0.5.

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8. Repeat Q7, but use 3 separate plots. Remove the legend.

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9. Create a scatter plot -log(p value) on the y-axis and SNP location on the x-axis, coloring by chromosome number. This is known as a Manhattan plot. Use the code below to simulate data for the plot. Use the Set3 palette of qual type in scale_color_brewer for the color scheme.

n <- 10000 # number of genes
position <- 1:n
chromosome <- factor(rep(1:10, each=n/10))
p.value <- runif(n)
df <- data.frame(position=position, chromosome=chromosome, p.value=p.value)

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