Dear list,
I am currently performing a meta-analysis of different datasets (GEO GSE
series) and have been writing sample information as dcf format files
under the 'annotationData/samples' directory however this slows down
considerably the processing time of running any type of analysis. Here
is a short example ('testData') involving 10 HG-U133_Plus_2 .CEL files
where either no sample annotation files are present in the directory or
11 sample annotation files are present.
Is there a way I can reduce this overhead?
Many thanks.
James
remove ~/.Rcache, start R:
## running with 0 sample annotation files
library("aroma.affymetrix")
cdf <- AffymetrixCdfFile$byChipType("HG-U133_Plus_2");
system.time(cs <- AffymetrixCelSet$byName("testData", cdf=cdf));
user system elapsed
0.450 0.020 0.527
exit R, remove ~/.Rcache, start R:
## running with sample annotations (11 files)
library("aroma.affymetrix")
cdf <- AffymetrixCdfFile$byChipType("HG-U133_Plus_2");
system.time(cs <- AffymetrixCelSet$byName("testData", cdf=cdf));
user system elapsed
16.74 0.10 17.40
> sessionInfo()
R version 2.12.1 (2010-12-16)
Platform: x86_64-pc-linux-gnu (64-bit)
locale:
[1] LC_CTYPE=en_US.utf8 LC_NUMERIC=C
[3] LC_TIME=en_US.utf8 LC_COLLATE=en_US.utf8
[5] LC_MONETARY=C LC_MESSAGES=en_US.utf8
[7] LC_PAPER=en_US.utf8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.utf8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets tools methods
[8] base
other attached packages:
[1] aroma.affymetrix_1.8.0 aroma.apd_0.1.7 affxparser_1.22.0
[4] R.huge_0.2.0 aroma.core_1.8.1 aroma.light_1.18.2
[7] matrixStats_0.2.2 R.rsp_0.4.0 R.cache_0.3.0
[10] R.filesets_0.9.1 digest_0.4.2 R.utils_1.6.0
[13] R.oo_1.7.4 R.methodsS3_1.2.1
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