Hi,
i have used rcorr() for calculating pearsons r and according p-values
for my data, giving me 2 matrices.
Now I would like to print scatterplots for all results with "good"
correlation values.
So i need a way to extract the row-name and column-name for each item in
the matrix with "good" r-values, so i can use them in the
plot()-function on my original dataframe programmatically.
below is what i have got - and now i'm stuck:
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incomingData <- read.csv(inputfile, header=TRUE, na="NA")
datamatrix <- data.matrix(incomingData)
library(Hmisc)
output <- rcorr(datamatrix, type="pearson")
# get short variables to ease reading
r <- output$r
n <- output$n
P <- output$P
r[n<5]<-NA # ignore less than five observations
r[r>-0.5 & r<0.5]<-NA # take only "good" korrelations
P[is.na(r)]<-NA # delete P values for deleted korrelations
r <- format(round(cbind(rep(-1.11, ncol(r)), r), 2))[,-1] ## trunctuate
matrix with correlations to 2 decimals
P <- format(round(cbind(rep(-1.11, ncol(P)), P), 4))[,-1] ## trunctuate
matrix with P-Values to 4 decimals
make_plot <- function(a,b,Rval,Pval,aname,bname) {
png(paste(aname,'_vs_',bname,'.png', sep=""))
plot(a,b, main="Rval(p=Pval)")
fitline <- lm(a~b)
abline(fitline)
dev.off()
}
-------------------------------------
Big Thanks for any ideas on this, Alex
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