Introduction

Racial disparities in healthcare has long been an issue with little progress and too many deaths. The methods by which treatments and detection of illnesses are developed is non-inclusive as evidenced by the data collected in this paper. Written by Alice B. Popejoy and Stephanie M. Fullerton, Genomics is failing on diversity discusses how Genome-wide association studies (GWAS), a method used to gather data about the variants associated with disease trails, used participants of which 96% were of European ancestry. Participants of Non-European ancestry such as African, Native and Hispanic and Latin American Ancestries made up only 4%. The process was repeated in 2016 as the the proportion of samples used in GWAS form non-European ancestry was said to have increased five fold. This increase, however, was in largely in that of the Asian population.

Create data

Ancestry_label1<-c("European ancestry","Asian","Other Non-European")
euro_asian_non_euro2009<-c(96,3,1)

Ancestry_label2<-c("European/nancestry","Asian/nancenstry","Other/nnon-European/nancestry")
euro_asian_non_euro2016<-c(81,14,5)

Pie graphs

# set up par()
par(mfrow = c(1,2), mar = c(2,3,1,5))


#pie graphs 1
# add main, init.angle, radius, and col
pie(euro_asian_non_euro2009, main= 2009, init.angle = -82, radius = 1, labels= Ancestry_label1, col= c(1,2,3))

# pie graph 2
# add main, init.angle, radius, and col
pie(euro_asian_non_euro2016, main= 2009, init.angle = -82, radius = 1, labels= Ancestry_label1, col= c(1,2,3))

Bar graphs

If you want, you can examine this code below to see how stracked bar graphs are made

# data
dat2016 <- c(14, 3,1,0.54,0.28,0.08,0.05)
dat2016_rev <- rev(dat2016)
barplotdata2016 <- matrix(c(dat2016_rev))

# labels
labels_x <- rev(c("Asian","African","Mixed", "Hispanic &\nLatin American",
                        "Pacific Islander","Arab & Middle East","Native peoples"))

par(mfrow = c(1,1))

barplot(barplotdata2016,
        width = 0.01, 
        xlim = c(0,0.1),
         axes = F,
        col = c(1,2,3,4,5,6,7),
        legend.text = labels_x)