[R] In need of help with correlations

[Tóth Dénes]

I do not know the bioconductor packages you mentioned, but the corr.test
function in the psych package, or the rcorr function in the Hmisc package
should do the work.
Also note that the c() in method=c("pearson") is redundant. Just write
method="pearson" instead (or nothing, since this is the default for both
functions).

HTH,
  Denes


> I am in need of someone's help in correlating gene expression. I'm
> somewhat
> new to R, and can't seem to find anyone local to help me with what I think
> is a simple problem.
>
> I need to obtain pearson and spearman correlation coefficients, and
> corresponding p-values for all of the genes in my dataset that correlate
> to
> one specific gene of interest. I'm working with mouse Affymetrix Mouse 430
> 2.0 arrays, so I've got about 45,000 probesets (rows; with 1st column
> containing identifiers) and 30 biological replicates (columns; with the
> top
> row containing the header information).
>
> I've looked through several Intro manuals and the R help files.
>
> I know that "cor(x,y, use ="everything", method = c("pearson")) " can help
> obtain the coefficients.
>
> I also know that "cor.test()" is supposed to test the significance of a
> single correlation coefficients.
>
> I've also found the bioconductor package "genefilter" / "genefinder" that
> looks for correlations to a given gene (although I can't get it to work).
>
> So far I've been able to:
>
> #Read in the csv file
> data<-read.csv("my data.csv")
>
> #Check the dimensions, names, class, fix(data)  to ensure the file was
> loaded properly
> dim(data)
> names(data)
> class(data)
> fix(data)
>
> #So far I've been able to successfully correlate the entire 'column'
> matrix
> through:
> x <- data[,2:30]
> y <- data[,2:30]
>
> corr.data<-cor(x,y, use = "everything", method = c("pearson"))
>
> write.csv(corr.data, file = "correlation of my data by columns.csv")
>
> -----------------------------------
>
> Now if I try and run the 'cor.test()' function on the same matrix, I get
> and
> error message with 'x' must be a numeric vector. This I don't understand.
> And this is not my goal, but rather me trying to learn how to go about
> doing
> correlation analysis in R.
>
> I've also tried transposing the data.frame using "as.data.frame(t(data))"
> and doing so gives the same error message as above.
>
> Can anyone help me with figuring out how to conduct a correlation analysis
> for specific gene/probeset, and help me understand why I get the above
> error
> message? I know it probably is a simple analysis, that is probably just
> over
> my head right now since I'm still new to R. But I can't figure it out and
> have been trying with a bunch of different variations for the past week.
>
> Thank you in advance for your help.
>
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>
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