Entering edit mode
Alex Koeppel
▴
20
@alex-koeppel-6039
Last seen 10.3 years ago
Hello everyone,
I'm analyzing some RNASeq in R 3.0.0 using DESeq 1.12.0. I need to do
a
variance stabilizing transformation of my count data so that I can do
a
Principal Components Analysis.
I plotted the distributions first, using plotDispEsts() and I had
estimated
the dispersions using estimateDispersions() with the default method
and
those both seemed to work fine.
However, when I do estimateDispersions(method="blind") on the same
input, I
get the following error:
"Error in parametricDispersionFit(means, disps) :
Parametric dispersion fit failed. Try a local fit and/or a pooled
estimation. (See '?estimateDispersions')"
I tried using method="pooled", as the message recommends, and that did
work, but I'm not completely sure if it is ok to use the pooled
results for
my PCA or not.
I'm looking for advice as to whether I should proceed with the pooled,
or
if there's something else I need to do to get the blind to work? If I
understand the documentation correctly, both blind and pooled, result
in a
single dispersion value for all samples, so I think I should be ok
with
pooled, but I wanted to double check that this is the best course of
action.
Thanks so much.
Alex Koeppel
P.S.
sessionInfo()
R version 3.0.0 (2013-04-03)
Platform: x86_64-apple-darwin10.8.0 (64-bit)
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] grid parallel stats graphics grDevices utils
datasets
methods base
other attached packages:
[1] gplots_2.11.0.1 MASS_7.3-26 KernSmooth_2.23-10
caTools_1.14
[5] gdata_2.12.0.2 gtools_2.7.1 vsn_3.28.0
DESeq_1.12.0
[9] lattice_0.20-15 locfit_1.5-9.1 Biobase_2.20.0
BiocGenerics_0.6.0
[13] BiocInstaller_1.10.1
loaded via a namespace (and not attached):
[1] affy_1.38.1 affyio_1.28.0 annotate_1.38.0
AnnotationDbi_1.22.5
[5] bitops_1.0-5 DBI_0.2-7 genefilter_1.42.0
geneplotter_1.38.0
[9] IRanges_1.18.1 limma_3.16.4 preprocessCore_1.22.0
RColorBrewer_1.0-5
[13] RSQLite_0.11.3 splines_3.0.0 stats4_3.0.0
survival_2.37-4
[17] tools_3.0.0 XML_3.95-0.2 xtable_1.7-1
zlibbioc_1.6.0
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