package plotrix: how to account for two two z categories

Thank you Jim, that is really nice!
But is there a way to use dots instead of boxes? and how do I control
the colours?
Best regards
Luigi

On Thu, Sep 24, 2020 at 9:29 AM Jim Lemon <drjimlemon at gmail.com> wrote:

Hi Luigi,
To display a nested breakdown like this I would suggest barNest. This
is one way to display the nesting. Note that if you change the order
of the factors in the formula you will get a different plot, so think
about how you want the summaries nested. Error bars can only be
displayed on the final breakdown.

# because you have fairly long labels, use a wide plot
x11(width=10)
barcol<-list("lightgray",c("#ff00ff","#ff99ff"),
 c("#00ff00","#66ff66"),c("#aaaa00","#888800"))
barNest(y~x+z+w,Q,main="Double Measurement",
 ylab="Response",col=barcol,errbars=TRUE)

Jim

On Wed, Sep 23, 2020 at 10:48 PM Luigi Marongiu
<marongiu.luigi at gmail.com> wrote:

Hello,
I have an experiment measuring optical density (OD) when comparing
three parameters:
a) concentration of the target
b) concentration of the probe
c) concentration of the reporter antibody.
Using plotrix I can nicely draw the first two into clusters, but I
can't get separation for the third parameter. is there a way in
plotrix to custer data according to two, let's say, z parameters (I
call the second high-level parameter as w)? For instance, two
clusters, each separated into two subclusters. Or is this more a job
for lattice?
Thank you.

```
x = rep(c(rep("1000 pmol", 4), rep("0 pmol", 4)),2)
z =  rep(c(rep("Treated", 2), rep("Untreated", 2), rep("Treated", 2),
rep("Untreated", 2)))
w = c(rep("1:1000", 8), rep("1:2000", 8))
y = c(1.18, 1.22, 1.52, 2.37, 0.97, 1.08, 1.17, 1.58, 1.16, 1.16, 2.27, 2.24,
      1.26, 1.28, 1.39, 1.77)
Q = data.frame(x, z, w, y, stringsAsFactors = FALSE)
names(Q) = c("[Target]", "Enzyme", "[Antibody]", "OD")
names(Q) = c("x", "z", "w", "y") # for ease, I'll use single letters
library(plotrix)
brkdn.plot(y~x+z, data=Q,
           pch = c(1, 16), cex = 1.5, type="p",
           main="Single Measurement",
           xlab=expression(bold("S1 nuclease")),
           ylab=expression(bold("Optical density")))
brkdn.plot(y~x+z+w, data=Q,
           pch = c(1, 16), cex = 1.5, type="p",
           main="Double Measurement",
           xlab=expression(bold("S1 nuclease")),
           ylab=expression(bold("Optical density")))
```

--
Best regards,
Luigi