From: Adaikalavan Ramasamy (firstname.lastname@example.org)
Date: Fri 14 Mar 2003 - 19:53:52 EST
I fit independent GLMs for a 2x2 factorial problem on the data matrix of
size 9500 x 12 (genes x arrays) and get 9500 observed t-values using the
apply() function. Now, I wish to get the permutated p-values. Therefore
I random sample the class labels and perform the glm fitting to get the
t-values from which I can get the p-values. This is done using a for()
loop. Is there a more efficient way to do this. Each loop currently
takes 5 minutes approximately.
More importantly I need to repeat this at least 1000 times which
requires 3-4 days but the process halts after some time.
To isolate the problem, I rewrote the script with 10 chunks of 100
loops. The first 2 chunk runs fine and the results are ok but on the
third (sometimes fourth, fifth or sixth) chunk, I get the following
Error in FUN(newX[, i], ...) : subscript out of bounds
Does R have a "time out" when I use 'R --no-save < script.file' on the
UNIX platform ?
I have checked with my system administrator and according to him there
is no upper limit to process time. I have explicitly removed every
unneccassary object at the end of each loop to keep the reserve memory.
I have tried the same on Windows and different chunks sizes and
different machines. Sometime it runs fine to completion and when it dies
it does not appear systematic.
Now I am reduced to writing scripts with chunks of 100 loops and then
collecting the chunks that were successful. I have to repeat the 1000
loops for many many different experiments and it is getting very
If you have any idea or had similar experience, please let me know.
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