Dear R ExpeRts,
I'm having memory difficulties using mahalanobis distance to trying to cluster
in R. I was wondering if anyone has done it with a matrix of 6525x17 (or
something similar to that size). I have a matrix of 6525 genes and 17 samples.
I have my R memory increased to the max and am still getting "cannot allocate
vector of size" errors. My matrix "x" is actually a transpose of the original
matrix (as I want to cluster by samples and not genes). "y" is a vector of the
mean gene expression levels and "z" is the covariance matrix of "x" (I think
this is where the problem lies as the covariance matrix is enormous.
I can't really provide a reproducible example as I would have to attach my data
files, which I don't think anyone would appreciate.
rm(list=ls()) #removes everything from memory#
gc() #collects garbage#
memory.limit(size = 4095) #increases memory limit#
x <- as.matrix(read.table("x.txt", header=TRUE, row.names=1))
y <- as.matrix(read.table("y.txt", header=TRUE, row.names=1))
z <- as.matrix(read.table("z.txt", header=TRUE, row.names=1))
mal <- mahalanobis(x, y, z)
The ultimate goal is to run "hclust" with the mahalanobis distance matrix.
If anyone knows where I could find a more "memory friendly" function or any
advise as to what I might try to optimize my code, I would appreciate it.
sessionInfo() is below.
Many Thanks,
_____________________________________________
Patrick Richardson
Biostatistician - Program of Translational Medicine
Van Andel Research Institute - Webb Lab
333 Bostwick Avenue NE
Grand Rapids, MI 49503
R version 2.8.0 (2008-10-20)
i386-pc-mingw32
locale:
LC_COLLATE=English_United States.1252;LC_CTYPE=English_United
States.1252;LC_MONETARY=English_United
States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices datasets tcltk utils methods base
other attached packages:
[1] svSocket_0.9-5 svIO_0.9-5 R2HTML_1.59 svMisc_0.9-5 svIDE_0.9-5
loaded via a namespace (and not attached):
[1] tools_2.8.0
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