I think something like this should do it, but I can't test without data:
rownames(mydata) <- mydata[,1] # Put the elements in the first column
as rownames
mydata <- mydata[,-1] # drop the things that are now rownames
Michael
On Thu, Nov 17, 2011 at 9:23 AM, Musa Hassan <musah...@gmail.com> wrote:
> 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.weyla...@gmail.com>
> wrote:
>>
>> On Wed, Nov 16, 2011 at 11:22 PM, muzz56 <musah...@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+s789695n4078114...@n4.nabble.com> wrote:
>> >
>> >> > -----Original Message-----
>> >> > From: [hidden
>> >> > email]<http://user/SendEmail.jtp?type=node&node=4078114&i=0>[mailto:
>> >> r-help-bounces@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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