Error: cannot allocate vector of size ...
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@wall-dennis-paul-1687
Last seen 10.3 years ago
I am trying to run the pam algorithm for k-means clustering, but keep getting the error "Error: cannot allocate vector of size 1048384 K" Any help on how to fix this would be greatly appreciated. Cheers, Dennis
Clustering Clustering • 4.6k views
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@james-w-macdonald-5106
Last seen 1 day ago
United States
Wall, Dennis Paul wrote: > I am trying to run the pam algorithm for k-means clustering, but keep > getting the error "Error: cannot allocate vector of size 1048384 K" > > Any help on how to fix this would be greatly appreciated. That error means you are running out of RAM. The quickest, best fix is to get more. Best, Jim > > > Cheers, > > Dennis > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- James W. MacDonald, M.S. Biostatistician Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623 ********************************************************** Electronic Mail is not secure, may not be read every day, and should not be used for urgent or sensitive issues.
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Hi Paul, If you've followed that advice or you've already got plenty of RAM you can try the command: memory.limit(2048) This should allow R to use 2Gb of RAM (the max it can use on a normal Windows machine), rather than the 1Gb it defaults too. Mike Smith > Wall, Dennis Paul wrote: > > I am trying to run the pam algorithm for k-means clustering, but keep > > getting the error "Error: cannot allocate vector of size 1048384K" > > > > Any help on how to fix this would be greatly appreciated. > > That error means you are running out of RAM. The quickest, best fix is > to get more. > > Best, > > Jim > > > > > > > > Cheers, > > > > Dennis > > > > _______________________________________________ -- Computational Biology Group Hutchison / MRC Research Centre Department of Oncology University of Cambridge Hills Rd, Cambridge CB2 2XZ Email: mls40 at cam.ac.uk
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I'm not sure if this will help, but this is an exerpt from the affy vignette: 5. Read in the data and create an expression, using RMA for example. R> Data <- ReadAffy() ##read data in working directory R> eset <- rma(Data) Depending on the size of your dataset and on the memory available to your system, you might experience errors like 'Cannot allocate vector . . . '. An obvious option is to increase the memory available to your R process (by adding memory and/or closing external applications2 . An another option is to use the function justRMA. R> eset <- justRMA() This reads the data and performs the 'RMA' way to preprocess them at the C level. One does not need to call ReadAffy, probe level data is never stored in an A?yBatch. rma continues to be the recommended function for computing RMA.
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