On Thu, 14 Feb 2008, SNN wrote:
>
> Thanks for the advice.
>
> I tried to find the cov of my matrix using R and it ran out of memory.
How did you do this? The covariance matrix is only 115x115, so it
shouldn't run out of memory
cov(t(code))
should work
If that doesn't work then
tcrossprod
> larger data sets where the entire data matrix doesn't fit in memory, you
> need some sort of double loop.
>
> -thomas
>
>
>> Zhaoming
>> -Original Message-
>> From: SNN [mailto:[EMAIL PROTECTED]
>> Sent: Wednesday, February 13, 2008 9
d some sort of double loop.
-thomas
> Zhaoming
> -Original Message-
> From: SNN [mailto:[EMAIL PROTECTED]
> Sent: Wednesday, February 13, 2008 9:14 PM
> To: r-help@r-project.org
> Subject: [R] Principal component analysis PCA
>
>
> Hi,
>
> I am tryin
Try EIGENSTRAT http://www.nature.com/ng/journal/v38/n8/abs/ng1847.html
or use a subset of SNPs.
Zhaoming
-Original Message-
From: SNN [mailto:[EMAIL PROTECTED]
Sent: Wednesday, February 13, 2008 9:14 PM
To: r-help@r-project.org
Subject: [R] Principal component analysis PCA
Hi,
I
Hi,
I am trying to run PCA on a set of data with dimension 115*300,000. The
columns represnt the snps and the row represent the individuals. so this is
what i did.
#load the data
code<-read.table("code.txt", sep='\t', header=F, nrows=30)
# do PCA #
pr<-prcomp(code, retx=T, center=T)
I a
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