I have made a graph with four growth curves using ggplot2.
Hopefully the code below should produce the graph if anyone wants to try.
I want to find a value for the maximum slopes on each of the lines, taken over say 4 time points.
Can anyone give any ideas how to go about this?
library(ggplot2)
dat <- structure(list(TIME = c(0L, 2L, 4L, 6L, 8L, 10L, 12L, 14L, 16L,
18L, 20L, 22L, 24L, 26L, 28L, 30L, 0L, 2L, 4L, 6L, 8L, 10L, 12L,
14L, 16L, 18L, 20L, 22L, 24L, 26L, 28L, 30L, 0L, 2L, 4L, 6L,
8L, 10L, 12L, 14L, 16L, 18L, 20L, 22L, 24L, 26L, 28L, 30L, 0L,
2L, 4L, 6L, 8L, 10L, 12L, 14L, 16L, 18L, 20L, 22L, 24L, 26L,
28L, 30L), OD600 = c(0.2202, 0.2177, 0.2199, 0.2471, 0.2834,
0.357, 0.4734, 0.647, 0.898, 1.1959, 1.3765, 1.3978, 1.3948,
1.3928, 1.3961, 1.4018, 0.24, 0.2317, 0.2328, 0.2522, 0.2748,
0.3257, 0.4098, 0.5455, 0.7387, 0.9904, 1.2516, 1.3711, 1.3713,
1.3703, 1.3686, 1.3761, 0.2266, 0.2219, 0.2245, 0.2401, 0.2506,
0.2645, 0.3018, 0.3484, 0.4216, 0.5197, 0.666, 0.872, 1.1181,
1.2744, 1.3079, 1.2949, 0.2389, 0.2242, 0.2315, 0.2364, 0.2372,
0.2373, 0.2306, 0.2385, 0.236, 0.2331, 0.2379, 0.2334, 0.2336,
0.2339, 0.2389, 0.2349), MMS = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0.005, 0.005, 0.005, 0.005, 0.005, 0.005, 0.005,
0.005, 0.005, 0.005, 0.005, 0.005, 0.005, 0.005, 0.005, 0.005,
0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01,
0.01, 0.01, 0.01, 0.01, 0.01, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02,
0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02)), .Names = c("TIME",
"OD600", "MMS"), class = "data.frame", row.names = c(NA, -64L
))
graph = ggplot(data=dat, aes(x=TIME, y=OD600))
graph + geom_line(aes(colour=factor(MMS)), alpha=1) +
opts(title="Log growth curves: change in cell density with increasing concentrations of MMS")+
scale_y_log10()
Many thanks
Something like this?
cbind(
MMS = unique(dat$MMS),
do.call(
rbind,
lapply(
unique(dat$MMS),
function(x) {
tdat <- dat[dat$MMS == x, ]
response <- tdat$OD600
timepoints <- tdat$TIME
rise <- (response[4:length(response)] - response[1:(length(response) - 3)])
run <- (timepoints[4:length(timepoints)] - timepoints[1:(length(timepoints) - 3)])
slopes <- c(rep(NA, 3), rise/run)
return(
list(
max_slope = max(slopes, na.rm = T),
time = timepoints[which(slopes == max(slopes, na.rm = T)) - 3]
)
)
}
)
)
)
Gives:
MMS max_slope time
[1,] 0 0.1215833 14
[2,] 0.005 0.1176833 14
[3,] 0.01 0.1014 20
[4,] 0.02 0.002166667 2