r - Add datapoints to existing scatterplot -

i have existing ggplot2 scatterplot shows results of parameter against normal database. want add 2 additional points graph pass command line arguments script script age value1 value2. show these points red r , l geom_text above each point. have following code far not know how add finishing touches

pkgload <- function(x)   {     if (!require(x,character.only = true))     {       install.packages(x,dep=true, repos='http://star-www.st-andrews.ac.uk/cran/')       if(!require(x,character.only = true)) stop("package not found")     }    }  pkgload("ggplot2") #load current normals database df<-data.frame(read.csv("dat_normals.txt", sep='\t', header=t))  args<-commandargs(true)  #specify each argument age <- args[1] rsbr <- args[2] lsbr <- args[3]  # run regression , append prediction intervals lm_fit = lm(sbr ~ age, data = df) sbr_with_pred = data.frame(df, predict(lm_fit, interval='prediction'))     p <- ggplot(sbr_with_pred, aes(x=age, y=sbr)) +            geom_point(shape=19, alpha=1/4) +           geom_smooth(method = 'lm', aes(fill = 'confidence'), alpha = 0.5) +           geom_ribbon(aes(y = fit, ymin = lwr, ymax = upr,                           fill = 'prediction'), alpha = 0.2) +            scale_fill_manual('interval', values = c('green', 'blue')) +           theme_bw() +            theme(legend.position = "none")    ggsave(filename=paste("/home/data/wolf/fv_dat/dat_results.png",sep="")) browseurl(paste("/home/data/wolf/fv_dat/dat_results.png",sep"")) 

essentially, want see if 2 new points fall within 95% confidence intervals normal database (blue ribbon)

your example not reproducible. constructive create data , reproducible example. not waste of time. solution, write said in comment. add new layer new data.

  newdata <- data.frame(age = args[1],                         sbr = c(args[2],args[3]))   p + geom_point(data=newdata,colour="red",size=10) 

for example:

sbr_with_pred <- data.frame(age = sample(15:36,50,rep=t), sbr = rnorm(50))

p <- ggplot(sbr_with_pred, aes(x=age, y=sbr)) +    geom_point(shape=19, alpha=1/4) +   geom_smooth(method = 'lm', aes(fill = 'confidence'), alpha = 0.5)     args <- c(20,rnorm(1),rnorm(2))   newdata <- data.frame(age = args[1],                         sbr = c(args[2],args[3]))   p + geom_point(data=newdata,colour="red",size=10)