Sorry, I forgot to include sessionInfo
> sessionInfo()
R version 2.11.1 (2010-05-31)
x86_64-pc-linux-gnu
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=C LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] sfit_0.1.9 ACNE_0.4.2 MASS_7.3-7
[4] aroma.affymetrix_1.7.0 aroma.apd_0.1.7 affxparser_1.20.0
[7] R.huge_0.2.0 aroma.core_1.7.0 aroma.light_1.18.2
[10] matrixStats_0.2.2 R.rsp_0.4.0 R.cache_0.3.0
[13] R.filesets_0.9.0 digest_0.4.2 R.utils_1.5.3
[16] R.oo_1.7.4 R.methodsS3_1.2.1
loaded via a namespace (and not attached):
[1] tools_2.11.1
Thanks,
Oscar
Hi all,
I'm trying to normalize several thousands of tumor samples using aroma. The
BAF profiles I get using
> AvgCnPlm(csN, mergeStrands=TRUE, combineAlleles=FALSE)
are quite noisy, so I have started using ACNE for getting 'cleaner' ones.
The problem is that I don't want to use the tumors as a reference, because
some of them have a lot of alterations. With aroma I used the 'target=0'
option to get log intensities and then I normalized them against my pool of
normals or against them matched normal if available just subtracting the
values.
For ACNE it seems I have to specify the reference, so I created folders for
each of my matched pairs and used
> NmfSnpPlm(csN, mergeStrands=TRUE, refs=c(FALSE, TRUE))
To indicate that the second array is the normal and the first the tumor.
Is this the best way to proceed in my situation?
The former command produces the following values for chromosome 2:
> summary(data)
total freqB
Min. : 0.0 Min. : NA
1st Qu.: 0.0 1st Qu.: NA
Median : 905.6 Median : NA
Mean : 2345.2 Mean : NaN
3rd Qu.: 4192.8 3rd Qu.: NA
Max. :53200.6 Max. : NA
NA's :153732
So it's clear that I'm doing something wrong. Does anyone know what is it?
Thanks in advance,
Oscar
Oscar M. Rueda, PhD
Postdoc, Breast Cancer Functional Genomics
Cancer Research UK Cambridge Research Institute
Li Ka Shing Centre
Robinson Way
Cambridge CB2 0RE
England
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