Pairwise correlation

Hi Michael,
Thanks for the response. I have noticed that the error occurred during my
data read. It appears that the rownames (which when the data is transposed
become my colnames) were converted to numbers instead of strings as they
should be. The original header names don't change, just the rownames. I have
to figure out how to import the data and have the strings not converted.
Right now am using:
mydata = read.csv(mydata.csv, headers=T,stringsAsFactors=F)

then to convert the data frame to matrix
mydata=data.matrix(mydata)

Then I just do the correlation as Peter suggested.

expression=cor(t(expression))

Thanks.

On 17 November 2011 08:51, R. Michael Weylandt <michael.weylandt at gmail.com>
wrote:

On Wed, Nov 16, 2011 at 11:22 PM, muzz56 <musahass at gmail.com> wrote:

Thanks to everyone who replied to my post, I finally got it to work. I
am
however not sure how well it worked since it run so quickly, but seems
like
I have a 2000 x 2000 data set.

Behold the great and mighty power that is R! Don't worry -- on a
decent machine the correlation of a 2k x 2k data set should be pretty
fast. (It's about 9 seconds on my old-ish laptop with a bunch of other
junk running)

?My followup questions would be, how do I get
only pairs with say a certain pearson correlation value additionally it
seems like my output didn't retain the headers but instead replaced them
with numbers making it hard to know which gene pairs correlate.

This is a little worrisome: R carries column names through cor() so
this would suggest you weren't using them. Were your headers listed as
part of your data (instead of being names)? If so, they would have
been taken as numbers.

Take a look at dimnames(NAMEOFDATA) -- if your headers aren't there,
then they are being treated as data instead of numbers. If they are,
can you provide some reproducible code and we can debug more fully.
The easiest way to send data is to use the dput() function to get a
copy-pasteable plain text representation. It would also be great if
you could restrict it to a subset of your data rather than the full 4M
data points, but if that's hard to do, don't worry.

You should have expected behavior like

X <- matrix(1:9,3)
colnames(X) <- c("A","B","C")
cor(X) # Prints with labels

Michael

On 16 November 2011 17:11, Nordlund, Dan (DSHS/RDA) [via R] <
ml-node+s789695n4078114h81 at n4.nabble.com> wrote:

-----Original Message-----
From: [hidden
email]<http://user/SendEmail.jtp?type=node&node=4078114&i=0>[mailto:

r-help-bounces at r-

project.org] On Behalf Of muzz56
Sent: Wednesday, November 16, 2011 12:28 PM
To: [hidden
email]<http://user/SendEmail.jtp?type=node&node=4078114&i=1>
Subject: Re: [R] Pairwise correlation

Thanks Peter. I tried this after reading in the csv (read.csv) and
converted the data to matrix (as.matrix). But when I tried the
correlation,
I keeping getting the error (x must be numeric) yet when I view the
data,
its numeric.

What does R tell you if you execute the following?

str(x)

Just because the data looks like it is numeric when it prints doesn't
mean
it is.


Dan

Daniel J. Nordlund
Washington State Department of Social and Health Services
Planning, Performance, and Accountability
Research and Data Analysis Division
Olympia, WA 98504-5204

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