In lrjoshi/gcplotR:

Virus Growth Curve in R

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("data") +
  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
}