[R] PCA analysis

[Daniel Malter]

I am not entirely sure after reading your email, but I thought you wanted to
do something like this:

###Start of example

###create random data for the example
x=rnorm(100,100,10)  ##create Xs
e=rnorm(100,0,5)     ##create Errors
y=x+e                ##create Ys

###plot
plot(y~x,pch=NA)     ##plot Ys against Xs but suppress all symbols (i.e.
plot invisibly)
text(y~x,labels=round(x),pch=NULL) ##use values of X (rounded to its integer
value) as symbols for the X-Y plot 

###End of example

So you could just substitute your variable names for x and y in the plot()
and text() commands. Let us know whether your problem is solved.

Cheers,
Daniel

-------------------------
cuncta stricte discussurus
-------------------------

-----Ursprüngliche Nachricht-----
Von: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] Im
Auftrag von Monna Nygård
Gesendet: Tuesday, June 17, 2008 5:04 AM
An: r-help at r-project.org
Betreff: [R] PCA analysis


Hi,
 
I have a problem with making PCA plots that are readable. 
I would like to set different sympols instead of the numbers of my samples
or their names, that I get plotted (xlabs). 
How is this possible? With points, i don4t seem to get the right data
plotted onto the PCA plot, as I do not quite understand from where it is
taken. I dont know how to plot the correct columns of the prcomp outcome
(p). 
I would really appreciate if someone could help me, I have struggled with
this for days now. How can I make a function that gives different symbols
for the points, depending on how big the number given to it as xlabs is?
 
Making the plots.
 
read.table(file = "S:\\SEDIM\\TRFLP\\B90-700.txt",sep="\t",
header=T)->boutbout <-bout[-1]p <- prcomp(bout) biplot(p, choices = c(2,3),
scale = 1, pc.biplot = FALSE, var.axes = F, ylabs = NULL,
xlabs=c("119","175","135","330","51","422","67","409","470","70","67","89","
135","215","330","409","470","51","80","119","175","222","301","422","280","
171","256","243","404","37","157","28","187","70","42","283","261","85","147
","204","235","411","514","77","204","87","366","306","351","371","38","534"
,"199","407","42","167","480","195","22","35","80","433","43","109","214","3
63","292","61","115","178","273","521","72","126","253","288","501","83","11
3","250","359","498","19","130","389","324","24","58","124","388","319","164
","101","153","383","345","219","179","161","375","298","450","555","439","5
4","54","490","465","411","18","85","503","455","394","179","187","416","447
","219","461","164","366","474","167","236","507","319","509","467","507","4
50","359","507","192","453","101","456","512","517"), cex=0.67,
main="90-700bp")
 
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