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Lecture 12 – Visualize data using R / ggplot2

Arvind R. Subramaniam

Assistant Member

Basic Sciences Division and Computational Biology Program

Fred Hutchinson Cancer Research Center

Contents

• Lecture 12 – Visualize data using R / =ggplot2=
• What you will learn over the next 3 lectures
• Example Datasets
• Raw Flow Cytometry Data
• Flow Cytometry Analysis Using =Tidyverse=
• =Tidyverse= Functions for Working with Tabular Data
• Use TSV and CSV file formats for tabular data
• Reading tabular data into R
• Read tabular data into a DataFrame (tibble)
• Plotting a point graph
• How do we show multiple experimental parameters?
• Plotting a point graph with color
• Plotting a line graph
• Plotting point and line graphs
• ‘Faceting’ – Plotting in multiple panels
• Play time!

What you will learn over the next 3 lectures

Loading, Transforming, Visualizing Tabular Data using Tidyverse packages

• readr
• ggplot2
• dplyr

Principles of Data Visualization (see book)

Example Datasets

Plate Reader Assay

Flow Cytometry

Raw Flow Cytometry Data

FSC.A	SSC.A	FITC.A	PE.Texas.Red.A	Time
79033	69338	9173	18690	3.02
101336	87574	13184	29886	3.04
51737	56161	3083	18324	3.06
79904	45085	9957	18099	3.08
124491	97305	15739	28730	3.09
54359	45015	6175	11918	3.11
64615	88989	11907	32413	3.13
109592	64132	12561	18824	3.15
58503	116384	11591	27629	3.19
38634	51511	7200	21930	3.21

5 cols × 2,720,000 rows

Flow Cytometry Analysis Using Tidyverse

Tidyverse Functions for Working with Tabular Data

Import/Export	Visualize	Transform
read_tsv	geom_point	select
write_tsv	geom_line	filter
	facet_grid	arrange
		mutate
		join
		group_by
		summarize

Use TSV and CSV file formats for tabular data

Tab-Separated Values:

strain   mean_yfp  mean_rfp  mean_ratio  se_ratio  insert_sequence  kozak_region 
schp674      1270     20316       0.561     0.004  10×AAG           CAAA         
schp675      3687     20438       1.621     0.036  10×AAG           CCGC         
schp676      2657     20223       1.177     0.048  10×AAG           CCAA         
schp677      3967     20604       1.728      0.03  10×AAG           CCAC         

Comma-Separated Values:

strain,mean_yfp,mean_rfp,mean_ratio,se_ratio,insert_sequence,kozak_region
schp674,1270,20316,0.561,0.004,10×AAG,CAAA
schp675,3687,20438,1.621,0.036,10×AAG,CCGC
schp676,2657,20223,1.177,0.048,10×AAG,CCAA
schp677,3967,20604,1.728,0.03,10×AAG,CCAC

Reading tabular data into R

library(tidyverse)

data <- read_tsv("data/example_dataset_1.tsv")

Read tabular data into a DataFrame (tibble)

library(tidyverse)

data <- read_tsv("data/example_dataset_1.tsv")

print(data, n = 5)

Comment your code

# library to work with tabular data
library(tidyverse)

# read the tsv file into a tibble and 
# assign it to the 'data' variable
data <- read_tsv("data/example_dataset_1.tsv")

# display the contents of 'data' 
print(data, n = 5)

Plotting a point graph

ggplot(data, aes(x = kozak_region,
                 y = mean_ratio)) +
  geom_point()

How do we show multiple experimental parameters?

strain	mean_ratio	insert_sequence	kozak_region
schp688	0.755	10×AGA	A
schp684	1.437	10×AGA	B
schp690	1.541	10×AGA	C
schp687	2.004	10×AGA	D
schp686	2.121	10×AGA	E
schp685	2.893	10×AGA	F
schp683	3.522	10×AGA	G
schp689	3.424	10×AGA	H
schp679	1.149	10×AAG	A
schp675	1.621	10×AAG	B
schp681	1.645	10×AAG	C
schp678	1.906	10×AAG	D
schp677	1.728	10×AAG	E
schp676	1.177	10×AAG	F
schp674	0.561	10×AAG	G
schp680	0.519	10×AAG	H

Plotting a point graph with color

ggplot(data, aes(x = kozak_region,
                 y = mean_ratio,
                 color = insert_sequence)) +
  geom_point()
  

Plotting a line graph

ggplot(data, aes(x = kozak_region,
                 y = mean_ratio,
                 color = insert_sequence,
                 group = insert_sequence)) +
  geom_line()

Plotting point and line graphs

ggplot(data, aes(x = kozak_region,
                 y = mean_ratio,
                 color = insert_sequence,
                 group = insert_sequence)) +
  geom_line() +
  geom_point()

‘Faceting’ – Plotting in multiple panels

ggplot(data, aes(x = kozak_region,
                 y = mean_ratio,
                 group = insert_sequence)) +
  geom_line() +
  geom_point() +
  facet_grid(~ insert_sequence)

Play time!

• Get used to the RStudio interface.
• Plot data and customize appearance.
• Learn how to “Knit” RMarkdown files.
• Learn more at https://ggplot2.tidyverse.org.