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### Visualization of hazard ratio's in TCGA data based on a single gene
### =================
# Goal: To visualize survival data (deaths) based on the expression level of a single gene
# as either high or low, and the hazard ratio between those two.
# Date: 2016-10-30
# Author: Mike Barnkob, www.mikebarnkob.dk
### Data
df_data <- data.frame(Cancer=c("Brain", "Colorectal", "Kidney clear cell carcinoma", "Kidney renal papillary carcinoma"),
HR=c(1.03, 0.98, 1.27, 1.22),
HR_lower=c(0.97, 0.62, 1.16, 1.03),
HR_upper=c(1.09, 1.55, 1.38, 1.45)
)
### Visualize
if (!require('ggplot2')) install.packages('ggplot2'); library('ggplot2') # Load ggplot2 library
#Based on http://www.gettinggeneticsdone.com/2011/03/forest-plots-using-rstats-and-ggplot2.html and https://github.com/hadley/ggplot2/issues/1441
#Layout inspired by Fivethirtyeight's election tables: http://projects.fivethirtyeight.com/2016-election-forecast/#margins
p <- ggplot(df_data, aes(x=Cancer, y=HR, ymin=HR_lower, ymax=HR_upper)) +
geom_linerange(size=8, colour="#a6d8f0") +
geom_hline(aes(x=0, yintercept=1), lty=1) +
geom_point(size=3, shape=21, fill="#008fd5", colour = "white", stroke = 1) +
scale_y_continuous(limits = c(0.5, 2)) +
coord_flip() +
ggtitle("Hazard Ratio for Gene of Interest") +
theme_minimal()
p
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