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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