#This Package Makes Virus Growth Curve
#data should be the table format as shown in Example
gcplotR<- function (data) {
colnames(data)
str(data)
data$MOI=as.factor(data$MOI)
data$hpi=as.factor(data$hpi)
#New data structure
str(data)
summary(data)
attach(data)
library(ggplot2)
library(plyr)
# Run the functions length, mean, and sd on the value of "change" for each group,
# broken down by sex + condition
cdata <- ddply(data, c("Cell","hpi","MOI"), summarise,
N = length(Titer),
mean = mean(Titer),
sd = sd(Titer),
se = sd / sqrt(N)
)
head(cdata)
View(cdata)
plot= function ()
#plot data
library(ggplot2)
# The errorbars overlapped, so use position_dodge to move them horizontally
pd <- position_dodge(0.5) # move them .05 to the left and right
#Changing Facet Level 0.1 to 0.1 MOI
levels(cdata$MOI) <- c("0.1 MOI", "10 MOI")
# The errorbars overlapped, so use position_dodge to move them horizontally
pd <- position_dodge(0.05) # move them .05 to the left and right
x=ggplot(cdata, aes(x=hpi, y=mean, colour=Cell, group=Cell)) +
geom_errorbar(aes(ymin=mean-se, ymax=mean+se), colour="black", width=.5, position=pd) +
geom_line(position=pd) +
geom_point(position=pd, size=2, shape=15, fill="white") + # 21 is filled circle
xlab("Hours post infection") +
ylab("Viral titer (log10)") +
scale_colour_hue(name="Cell type", # Legend label, use darker colors
breaks=c("OFTu", "STU"),
labels=c("OFTu", "STU"),
l=50) +
# Use darker colors, lightness=40
ggtitle("Growth Curve") +
expand_limits(y=0) + # Expand y range
scale_y_continuous(breaks=0:10*1) + # Set tick every 4
theme_bw(base_size = 16) +
theme(legend.justification=c(1,0),
legend.position=c(1,0))+facet_grid(.~MOI,scales="free") # Position legend in bottom right
x
}
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